can digital photography replace the visual assessment of bruise age?

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Can Digital Photography replace the Visual Assessment of Bruise Age? Martin R. Perrett 0

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The final report on my Photographic Science degree major project. While the practical work didn't go so well the research is pretty extensive and written with the intention that it covered both the medical and photographic aspects in a way that could be understood by each.Thought it may be useful in anyone happens to be hunting the web for research on a similar project on what would create a very useful forensic tool.

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Page 1: Can Digital Photography replace the Visual Assessment of Bruise Age?

Can Digital Photography replace the

Visual Assessment of Bruise Age?

Martin R. Perrett

B.Sc. in Photography & Digital Imaging

University of Westminster

August 2009

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Page 2: Can Digital Photography replace the Visual Assessment of Bruise Age?

Martin R. Perrett BSc Photographic Science and Digital Imaging

Table of Contents

i. Abstract.............................................. 4

ii. Hypothesis.......................................... 4

iii. Abbreviations...................................... 5

iv. Acknowledgements............................ 6

v. Introduction......................................... 7

1. The Role of Bruising in Forensic Science 8

1.1 What is a Bruise................................ 8

1.2 The Science of Bruising................... 8

1.3 The Appearance of a Bruise............. 9

1.4 The biochemistry of bruising and its repair 10

1.5 Visual assessment of a bruise......... 13

2. The Science of Colour............................ 16

2.1 Light................................................... 16

2.2 The human visual system................ 19

2.3 Colour Perception and Appearance 22

2.4 The inadequacies the human visual

system................................................ 23

2.5 Basics of Colour Reproduction....... 27

2.6 Metamerism....................................... 28

2.7 Colour matching and the CIE colorimetry

system............................................... 30

2.8 Colour Spaces and Colour Management 32

3. Measuring the colour of bruises.. 35

3.1 Spectrophotometry........................... 35

3.2 Colourimetry using tristimulus

Colourimetry..................................... 36

3.3 Colourimetry using digital cameras 37

Aims & Objectives.......................................... 40

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Martin R. Perrett BSc Photographic Science and Digital Imaging

4. Methods....................................................... 41

4.1 Apparatus.............................................. 41

4.2 Software................................................ 41

4.3 Bruise creation..................................... 41

4.4. Image Capture..................................... 43

4.5 Measuring the Colour Chart................ 48

4.6 Pre-processing..................................... 48

4.7 Processing................................................... 50

4.8 Characterization Error......................... 54

5. Experimental and results........................... 56

5.1 Bruising.................................................. 56

5.2 Illumination............................................ 57

5.3 Colour Chart Measurements................ 58

5.4 Bruise changes with time..................... 59

5.5 Characterisation and Error................... 60

6. Discussion.................................................. 60

7. Conclusions................................................ 63

References.................................................. 64

Appendices............................................... 65

1. Colour Chart......................................... 66

2. Calibrating the Spectrophotometer... 66

3. Colour chart and greyscale Readings 68

4. Reproducibility data............................. 69

5. Bruise infliction times.......................... 70

6. Camera Settings................................... 70

7. Times and dates of photographs of bruise BL 718. Times and dates of photographs of bruise BU 719. Times and dates of photographs of bruise ML 7210.Times and dates of photographs of bruise MR 7311.Function for the extraction of data from

grey scale and colour chart..................... 73

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Martin R. Perrett BSc Photographic Science and Digital Imaging

N.B. All images are in public domain unless otherwise stated. Images are reproduced as .jpg and printed on a colour laser printer. High quality images of results are provided on the DVD that accompanies.

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Martin R. Perrett BSc Photographic Science and Digital Imaging

i. Abstract

It is well known that bruises change in colour as they dissipate over time. The

biological processes that return the skin to its regular state are well understood

and known to be the cause of this colour change. There seems to have been a

general acceptance in the medical and forensic communities that the age of a

bruise can be determined by the inspection of different colours present in the

bruise. Estimation of the age of a bruise is usually preformed by forensic

experts whose observations can have legal consequences.

This view has come in to question in recent publications1 and also proven to be

unreliable in two recent undergraduate studies2,3 performed at Barts Hospital

Medical School. However the correlated results of a number of papers

documenting the changing colour of bruises over their duration do suggest that

there is a trend4 from this the simple conclusion is made that a more

quantitative analysis of the colours in bruises is required in order to gain any

conclusive evidence that bruise colour relates directly to age.

ii. Hypothesis

It is possible to extract useful colour information from digital images of bruises

taken with consumer digital cameras. The analyses of such information could

lead to an effective and scientifically valid method to accurately determine the

age of a bruise for forensic purposes.

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Martin R. Perrett BSc Photographic Science and Digital Imaging

iii. Abbreviations

A & E = Accident and Emergency (English equivalent of an Emergency Room)

CR2 = Canon Raw version 2 (file extension .CR2)

dpi = dots per inch

cm = centimetre, 10-2 m

CCD = Charge- coupled Device

CIE = Commission Internationale de l'Eclairage - the International

Commission on Illumination

CRT = Cathode Ray Tube

CVD = Colour vision deficiency

DVD = Digital Versatile Disc

EXIF- = Exchangeable image file format

FME = Forensic Medical Examiner

GUI = Graphical User Interface

ICC = International Colour Consortium

ISO = International Standard Organisation (referring to ISO 5800:1987 the

standard for measuring the speed of colour negative film)

JPEG = Joint photographic experts group (file extension .jpg)

K = Kelvin

LCD = Liquid Crystal Display

nm = nanometre, 10-9 m

PC = Personal Computer

RGB = Red, Green and Blue colour space

SPD = Spectral Power Distribution

sRGB = standard Red, Green and Blue colour space

TIFF = Tagged Image File Format (file extension .tif)

USB = Universal Serial Bus

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Martin R. Perrett BSc Photographic Science and Digital Imaging

iv. Acknowledgements

First would to thank all Margaret Pilling and Sophie Grossman whose projects

where the starting point.

Secondly I would like to thank my farther Prof. David Perrett for introducing me

to the work of Pilling and Grossman and his help in me understanding the

biochemical side of this study and his guidance in the writing of the final project

report.

I would also like to thank all my course staff for their guidance and support,

John Smith, Dr. Efthimia Bilissi, Elizabeth Allen and Dr. Sophie Triantaphillidou.

Lastly I would like to thank the subjects who took part.

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Martin R. Perrett BSc Photographic Science and Digital Imaging

v. Introduction

In his most recent review Langlois5 asked whether there was any science

behind the quest to determine the age of bruises. The aim of this dissertation

taken in conjunction with the studies of PillingError: Reference source not found

and GrossmanError: Reference source not found is to try and apply a scientific

approach to Langlois’ question. Since Pilling and Grossman were both critical of

the abilities of forensic medical examiners to visually age bruises with any

accuracy, this research has to been to try and develop a reliable methodology

using digital cameras. It is necessary to link research into the medical, forensic

and biochemical science of bruises with knowledge of photographic and colour

reproduction techniques in order to develop my approach.

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Martin R. Perrett BSc Photographic Science and Digital Imaging

1. The Role of Bruising in Forensic Science

1.1. What is a Bruise?

Everyone will have seen a bruise and more than likely suffered one. A bruise is

formed following a trauma, such as a bump, that does not break the skin but

damages the underlying blood vessels. Its appearance is due to the release of

blood into the skin or subcutaneous tissues6,7.

Figure 1.1: Types of bruises .The left hand image caused by an accident

(photo by M.R. Perrett), right hand image caused as a result of physical

violence (courtesy of Prof. P Vanezis).

1.2 The Science of Bruising

A bruise, also called a contusion, is defined as bleeding beneath intact skin and

it must not be confused with a bleed caused by other events, such as

venepuncture or at the site of an injection. Bruises are most commonly caused

by blunt force trauma but can also be caused by pressure changes. The trauma

in most cases will be accidental from both known and unknown causes.

Accidents can range from a simple un-noticed bump to a very serious injury due

to say a car crash. Bruises can also result from high contact sports such as

rugby, martial arts and boxing. Other causes of bruising are following many

hospital operations and some types of dental treatment. Some diseases, e.g.

haemophilia, and certain drugs, e.g. aspirin, can cause subcutaneous bleeding

which can cause bruises to appear without an injury having occurred.

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Martin R. Perrett BSc Photographic Science and Digital Imaging

Bruises often result from physical violence associated with criminal violence,

assault and abuse. Knowing the age of the bruise can be important evidence in

confirming whether or not a bruise resulted from such an attack. Currently it is

the role of a forensic medical examiner (FME) to estimate the age of the

bruise(s) with their professional opinion being used as evidence. Details such

as the location of the bruise and time and date of inspection of the bruising are

recorded. It is also essential that colour photography used to document the

bruising to ensure a permanent record of its appearance as this will change and

once the bruise has healed there will be no trace of it left on the subjectError:

Reference source not found. The photograph will then become of evidential

importance.

1.3 The Appearance of a Bruise

The development and appearance of a bruise depends on several factors

including:

Appearance of the skin: Skin colour is determined predominantly by the

amount of the brown pigment, melanin in the skin. This varies considerably with

ethnicity and also changes with exposure to sunlight. It is much more difficult to

observe bruises in individuals with darker skin colouration. Skin appearance is

also dependant on the degree of dilation of the blood vessels in the skin and

beneath it. This effect is seen more in individuals of lighter skin tone. Both the

production of melanin and the sub-cutaneous blood flow vary on different parts

of the body and variance in blood flow can also be due to scarring and burns.

Severity of the trauma: According to Shepherd8, the damage to blood vessels

and therefore amount of blood extravasated is proportional to the force applied.

This in turn would affect the depth below the surface at which injury has

occurred. Deeper bruises are obscured by the overlying tissues.

The area of the body: Vascularity of the underlying tissue, connective tissue

support and the amount of subcutaneous fat at the site of injury all affect the

development of a bruise. Bruising tends to occur more readily in highly

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Martin R. Perrett BSc Photographic Science and Digital Imaging

vascularised areas, as well as in those areas where there is loose tissue (e.g.

around the eyes or genitals) and more subcutaneous fat. This is opposed to

areas where the bone is close to the skin9,10 and bruising is difficult.

Age: Bruising tends to occur more easily in infants11 and the elderly. In infants,

there is an excess of loose skin and subcutaneous fat, whereas elderly

individuals tend to have poorly supported, and therefore fragile, blood vessels

that are more likely to rupture forming a bruise. Bruises in these age groups will

take longer to resolveError: Reference source not found.

Gender: Females tend to bruise more readily than males due to their greater

amounts of subcutaneous fatError: Reference source not found.

Illness: These includes bleeding disorders, supportive tissue disorders, and

other conditions that may lead directly to an altered level of bleeding or clotting,

or indirectly via changes to the blood vessels and surrounding structures.

Drugs: Many drugs, e.g. blood thinning drugs such as warfarin, even at

therapeutic levels, affect how readily bruises may form and heal. There are also

medical treatments for bruises such as arnica and witch-hazel that are said to

help increase the dissipation of a bruise.

1.4 The biochemistry of bruising and its repair.

Haemoglobin (figure 1.2) is the main protein in red blood cells and is

responsible for supplying oxygen to all parts of the human body. A haemoglobin

molecule consists of 4 smaller proteins known as globins: usually 2 alpha

globins and 2 beta globin. These 4 proteins are associated with a small iron-

containing molecule called haem (figure 1.3). The red colour of haemoglobin is

present when the iron in haem binds oxygen.

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Martin R. Perrett BSc Photographic Science and Digital Imaging

Figure 1.2. The structure of haemoglobin showing the alpha-globins (red) and

beta-globin (blue) and the haems are shown in green. Source Wikipedia

The force of a trauma damages the blood vessels under the skin. Once blood

has leaked in to the subcutaneous tissue the body immediately starts a process

to remove the blood. As the blood leaks into the surrounding tissue there is an

inflammatory response that starts the degradation and removal of the red

cellsError: Reference source not found. This is done first by recruiting anti-

inflammatory white blood cells, called macrophages, which digest the red blood

cells by a process known as phagocytosis. This breaks down red cells into their

constituent parts releasing the haemoglobin. The haemoglobin is then further

broken down releasing the haem, which is red-black in colour, and the

uncoloured globin molecules (figure 1.4). The haem then loses the iron atom

converting it in to biliverdin (figure 1.5). This is then further degraded to the

more open organic chemical structure called bilirubin (figure 1.6). It is these

processes that accounts for the colour changes seen as a bruise dissipates; the

haemoglobin and haem appear as red/purple/blue depending on the depth and

level of oxygenation. It is the presence of biliverdin that accounts for the green

colouration and the bilirubin for the yellow, which supports the forensic experts

who say that the appearance of yellow was of most significance when ageing

bruises. The released iron can also added to the colours observed being

somewhat black in colour.

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Haemoglobin

Biliverdin + :

Bilirubin

Haem + globins

Martin R. Perrett BSc Photographic Science and Digital Imaging

Figure 1.3. Schematic of the break down of haemoglobin indicating the colour

changes.

Figure 1.4 The structure of haem

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Martin R. Perrett BSc Photographic Science and Digital Imaging

Figure 1.5 The structure of Biliverdin

Figure 1.6 The structure of Bilirubin

1.5 Visual assessment of a bruise

When the age of a bruise is called into question in a criminal or coroners’ court,

a forensic medical expert or witness will be called to give their opinion. Their

opinion can, of course, have far-reaching medico-legal consequences. Such

witnesses are either, qualified forensic pathologists, specially qualified general

practitioners or, increasingly, specialist nurses. They are generally referred to

as forensic examiners. Currently there is no standardised methodology for

visually assessing the age of a bruise with forensic examiner using their

personal experience. Various forensic textbooks give guidance as to how to

estimate the age of a bruise. According to Langford et al12, in discussing bite

marks, specific colours can be related to the age of bruise as indicated in table

1.1. Bohnert et al13 used similar descriptions of bruise colouration.

ShepherdError: Reference source not found in the latest edition of the standard

work Simpson’s Forensic Medicine describes similar colour changes but

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Martin R. Perrett BSc Photographic Science and Digital Imaging

cautions against using them as a “clock” to age a bruise. He quotes “research in

the 1980’s showed that if yellow was identified, the bruise was over 18 hours

old, whereas if no yellow could be seen, the bruise could not be reliably aged”.

He further comments that “it is to be hoped that further research will elucidate

this matter.”

Table 1.1. Ageing of bruises by their colour (adapted from reference 11)

Age Colours

Initial Purple red / blue

1- 3 days Brown, greenish brown

4 - 5 days Greenish brown, greenish yellow

7 -10 days Yellowish brown, tan and yellow

Over 14 - 15 days Normal skin colour returns

According to the twenty three forensic experts interviewed by GrossmanError:

Reference source not found* in her survey, the following criteria are used when

visually assessing bruises. (The first number in the brackets denotes the

number of experts stating the criteria as relevant to their assessment).

1. Colour (23/23)

2. Size (6/23)

3. Intensity (17/23)

4. Other criteria named included swelling, texture such as “pitting”,

surrounding erythema (reddening of skin), sharpness of the edge and “gut

impression”. (6/23)

All the FMEs placed considerable emphasis on colour in their assessments.

“Yellow” and “red” colourations were said to have the most relevance with

purple, blue, brown and green also being citied as important by the forensic

* I was personally involved with these recent studies carried out by undergraduate medical students at Bart’s and the London School or Medicine and Dentistry, who were undertaking a forensic medicine course option research project.

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experts. This tends to agree with the biochemical break down in a bruise. The

initial leakage of blood under the skin appears as red or dark purple. The

haemoglobin then becomes oxidised and is degraded. These changes result in

yellow becoming present as haemoglobin breaks down into biliverdin

The same study asked 28 forensic experts, who supplied the above information

to assess the age of a selection of photographs of bruises of known ages. The

images showed only the area of skin that had been inflicted with a bruise via the

use of a suction pump and were un-doctored other than to remove identifying

marks. All the images had been taken with a digital SLR, and printed out by a

commercial photo-lab. These photographs were from a previous studyError:

Reference source not found* were every effort had been made to ensure that

the photographs were as standardised as possible by using flash photography

and including a colour chart used to aid the colour reproduction.

The accuracy of their estimates varied considerably with many being erroneous

to the extreme that some examiners can be out by as much as a month. Clearly

criminal convictions may indeed have resulted from the testimony provided by

expert witnesses. However it is now clear that the process used by FMEs is

itself very flawed and in need of replacement by a more reliable, preferably

accurate method. In order to do this we need knowledge of how colours can be

accurately defined and measured.

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2. The Science of Colour

Up until now in this dissertation, the term colour and other terms relating to it

have been used in a rather colloquial way. Munang14 found a marked variability

in colour description of bruise and severely questioned the practice of

estimating bruise age from photographs in child protection proceedings. In the

sixteen previous studies surveyed by Dimitrova et alError: Reference source not

found details of colours described by forensic experts in their visual assessment

of bruises resulted in nineteen different terms being used to describe colours:

such as blue-black; purple-black; dark purple; yellow-green; green; red; livid

red. This same problem can be seen in the study of GrossmanError: Reference

source not found. In the most extreme of examples of mis-ageing a bruise

reported in her study the forensic examiner might have unknowingly been

colour blind. The problem with using such descriptions is that the blue black

described in one study may differ from the blue black described by another or

the purple black used may differ between the two researchers.

There is no standardisation of this descriptive terminology. It becomes a

subjective viewpoint of the observer and/or researcher thus it is necessary to

talk about colour in a more exact, accurate, quantitative and scientific manner if

it is to be of use for the purposes of forensic analysis and evidence in court.

There are international commissions such as the CIE (The Commission

Internationale de L’Eclairage) and many detailed publications on the measuring,

imaging and reproduction of colour. In the following section I give an overview

of the areas of colour that are important so that this project is presented in a

clear and accessible manner.

2.1 Light

Electromagnetic radiation consists of streams of energy possessing photons or

varying wavelengths. Light is only a small part of the wider electromagnetic

spectrum. Visible light is electromagnetic radiation with wavelengths falling

between approximately 400 nm and 700 nm15, which can stimulate the human

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Martin R. Perrett BSc Photographic Science and Digital Imaging

visual system. Colour only exists in the perception of radiation with wavelengths

in this range. “White” light is only produced from a combination of this range of

wavelengths. Colour is attributed to light of more specific wavelengths as

commonly demonstrated by the splitting of white light into the visible spectrum

using a prism, diffraction grating or naturally in a raindrop forming a rainbow.

Sources of light can be described by their spectral power distribution (SPD)

which is the relative power of each wavelength emitted by the source. Because

they all differ it is necessary to normalise the spectral power distribution for

purposes of comparison. By definition this is performed by dividing the function

by the function’s value at 560 nm. Figure 2.1 illustrates the power from some

different sources of light. All the SPDs shown in figure 2.1 are perceived as

being “white” light. However it is clear, that looking at their SPDs, that some

evidently have more power towards the blue end of the spectrum whilst others

have more power at the red end. Yet others have intense spikes due to

including metals in the light source.

Figure 2.1 Spectral power distributions of three common illuminants

(Reproduced from reference Error: Reference source not found).

In figure 2.1 it is apparent that blue sky has increasingly more power towards

the blue end of spectrum while a tungsten filament lamp has increasingly more

energy towards the red end of the spectrum. The energy of mean noon sunlight

is more equally spread across the spectrum. The human visual system

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Martin R. Perrett BSc Photographic Science and Digital Imaging

compensates for these differences so that a “white” object appears white when

viewed under each of these light sources. Note that the SPDs are all equal as

they have been normalised at 560 nm.

Most objects do not themselves possess intrinsic “colour”. It is the interaction of

light with an object by absorbance, reflectance, scatter or transmittance that

gives objects their colour. An object can only interact with the wavelengths

incident upon it. For example an object that reflects red light when viewed using

light of blue wavelengths will appear black as it is unable to reflect any of the

incident wavelengths. However when object of is viewed under two differing

illuminants, that cover a sufficient range of the visible spectrum, for example

day light and tungsten, there is a tendency that it will appear the same colour

under both. This is known as colour constancy and is due to the cognitive

process known as colour adaption by which the neural processing of the brain

corrects for the differing spectral power distribution of a scene.

Figure 2.2 A picture of a bruise taken under an unknown illuminant with

the colour temperature set as left: 2800K (average tungsten) centre:

balanced to white background, right: 6500K (Average Daylight).

The difference in colour between the two light sources becomes apparent in the

imaging process (as shown in figure 2.2) as there is not yet a colour constancy

algorithm for computer vision that is effective as the human vision system16. It is

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Martin R. Perrett BSc Photographic Science and Digital Imaging

thus important in the reproduction of colour that colour temperature of the

illuminant is known. This is so called as it relates to the temperature at which a

blackbody radiator† will emit light that matches the chromaticity of the illuminant,

this is expressed in degrees Kelvin (K). While most everyday illuminants are not

produced by blackbody radiators their SPDs can be approximated to one, and is

this that determines the white-point or colour balance of a scene. Digital

cameras allow the user to set the white balance to a preset and most newer

models will have an “auto white-balance”. In order to ensure a scene has the

correct colour balance a reference white and ideally other neutral colours (grey

and black) should be present in the scene which can be used during a

processing phase to ensure the correct white point of the image.

2.2 The human visual system

The human visual system is a combination of the optics and the detectors within

the eye and the neural processing and cognition of signals sent from the eye to

the brain. Colour is only attributed to the perceived light due to the processing,

in the visual cortex of the brain, of the responses to light generated in the eye.

The full workings of this process are still not fully understood and so the

following section does contain a simplified explanation how colour is perceived

but with enough detail to give a sufficient understanding to help with the

comprehension of later sections.

† A blackbody radiator is an idealised object that emits an SPD dependent on its temperature.1 Nash, K.R., Sheridan D.J., (2009) Can One Accurately Date a Bruise? State of the Science. Journal of Forensic Nursing 5, 31-37

2 Pilling M., (2008) Visual Assessment of Bruise Age by Forensic Experts, BMedSci Project Dissertation, Barts & the London School of Medicine, Queen Mary University of London

3 Grossman S., (2009) Is the Objective Assessment of Bruise Age Possible? BMedSci Project Dissertation, Barts & the London School of Medicine, Queen Mary University of London

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Martin R. Perrett BSc Photographic Science and Digital Imaging

Figure 2.3 A cross-section of a typical human eye.

At the front of the eye the cornea and lens focus the light onto the cells of the

retina at the rear of the eye. The retina is covered with millions of light sensitive

cells of two types: rods and cones. Rods are reasonably efficient for detecting

low intensities levels of light and are more sensitive in the blue part of the

spectrum. This is why colours are less noticeable at night and tend to appear a

lighter blue than they do during the day. As light intensities increase the rods

are deactivated and the cones become the primary light sensors. Cones come

in three types, each of which is sensitive to a different range of wavelengths

(the relative sensitivities shown in figure 2.4). Fundamentally they are the colour

receptors. There are cones with peak sensitivities at short (440 nm), medium

(545 nm) and long wavelengths (580 nm)17‡ denoted as S, M and L respectively

‡ These values are still the subject of some debate but suffice here as rough guidelines.

4 Dimitrova T., Georgieva L., Pattichis C., Neofytou M. (2006) Qualitative Visual Image Analysis of Bruise Age Determination: A Survey, Proceedings of the 28th IEEE EMBS Annual International Conference, New York City, USA, 4840-4843

6 Capper C. (2001) The Language of Forensic Medicine: The meaning of some terms employed. Medicine, Science and the Law; 41:256-9

7 Knight B. (1992) Legal Aspects of Medical Practice. Fifth edition. Elsevier Health Sciences, London; 84

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each type containing a unique pigment. These correspond roughly to blue,

green and red, which is why they are also sometimes referred to as r, g and b

respectively and they can also be denoted by the Greek characters β, γ and ρ

respectively. The responses of the three sets of cones are combined and

transmitted to the visual cortex of the brain. The reduction of the spectrum into

just three responses is called trichromacy. It is trichromacy that gives rise to the

phenomena known as metamerism, were spectrally differing lights are

perceived to be the same colour18. This is the most important aspect of colour

vision in terms of being able to reproduce the wide variety of colours effectively.

This is explained in more depth throughout this section.

Figure 2.4 Normalised spectral sensitivities of the S, M and L cone types.

Figure 2.4 shows how the spectral sensitivities of the S, M and L cones over

lap, a great deal in the case of the M and L cones. Our ability to discriminate

colours is helped by this over lapping as well as the uneven numbers of each

cone type, the ratio of S:M:L cones being around is 6:3:119. The cones and rods

are distributed differently across the retina with only cones being present at the

fovea, which is located directly behind the lens. Away from the fovea the

number of cones and their density decrease. It is the foveal vision that is

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Martin R. Perrett BSc Photographic Science and Digital Imaging

responsible for perception of the viewing of fine detail that is picked up by the

foveal vision scanning a scene and picking out areas of interest. The cones and

rods do not send the signals they generate to the brain separately but rather

interconnect to form receptive fields. The signals sent to the brain are thus a

combination of responses from all three different cone types and rods to form

three types of receptive fields which send information to the visual cortex

through three opponent channels. It is this process that gives rise to the

opponent nature of vision as explained in the following section.

2.3 Colour Perception and Appearance

Figure 2.5 A schematic of the Munsell Color System showing how the

descriptive qualities of a colour, hue, chroma and lightness (value) relate

to each other

Using the idea of combining various amounts of red, green, and blue

trichromacy it can be hard to relate this to common descriptions of colour such

as a colour's hue, saturation and lightness. It is through the opponent nature of

vision that these characteristics of colour appearance can be related to the

process of how the spectrally differing light it is perceived. Of the three

opponent channels two are for the transmission of information to colour red

versus green and blue versus yellow. It is so called, because under normal

conditions, it is impossible to see a colour one could describe as a greenish-red

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or a yellowish-blue. The third channel relates achromatic information to the

brain, i.e. how light or dark the colour is. It also refers to the level of luminance

since again one cannot see something that is both light and dark

simultaneously. Figure 2.5 shows how these three channels can combine to

produce a method to arrange colours systematically, on three perpendicular

axes, one for each opponent channel. It can then be said that on the plane of

the yellow-blue and red-green axis colours vary with their distance from the

intersection in the middle with the lightness axis and the angle it is about the

intersection. The distance from the achromatic axis is either referred to as

chroma but would more commonly be described as the degree of saturation.

(These however along with other terms in italics here have mathematically

defined value as described in the next section.) That is to say that various

intensities of pink could be described as being heavily or lightly saturated reds.

It is when all the colours are fully saturated that they create a ‘band’ that

consists of the visible spectrum bent round so that the red end is joined the blue

via purple hues that do not appear in the spectrum. Using opponent principles

these hues can all be described as being bluish-greens, greenish-yellow,

yellowish-reds, reddish-blues etc. though we have more common names for

some of these such as orange and purple for example. Other than those hues

between red and violet all the hues can be related to a singular, or

monochromatic, wavelength of light. Thus all colours can be described in terms

of their lightness, saturation and hue, which is far more relevant than describing

colours as being so much red and so much green, especially as has just been

stated we cannot perceive certain colour combinations for example red and

green.

2.4 The inadequacies human visual system

Even in the area of colour research there is still not consistent use of words to

describe colour20. It cannot be assumed that forensic examiners will be well

versed in the terms they use to describe colour. While they are experts in

matters of medicine and forensic pathology it is highly unlikely they will also be

what are known as experienced colour observers. A prime example of this

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comes from the previously cited results of GrossmanError: Reference source

not found of bruise appearance where 17 of 23 forensic examiners stated that

the “intensity of bruise colour” was relevant to the age of a bruise. It is not clear

whether they are using this term as a synonym for lightness or for chroma. The

forensic textbooks referred to previouslyError: Reference source not foundError:

Reference source not foundError: Reference source not found do not mention

anything about the saturation or lightness of the colour terms they use. If an

effective standardised methodology for the visual assessment of bruises was to

be devised it would most likely have to take in to consideration the all physical,

physiological and psychological components of the human visual system.

Whether the bruise is viewed in vivo or in vitro (thus ignoring matters of

reproduction, which are below) the physical parameters must include the

spectral properties and intensity of the light under which the bruise is viewed

and any colours in the background or surrounding area. These relate more

directly to the psychological effects of the observer viewing images such the

colour constancy which is the process that keeps whites appearing white under

differing spectral distribution and colour memory, which adjusts how an

observer perceives a colour based on a memory of what is looks like.

The physiological effects include the level of adaptation from photopic (night)

vision to scotopic vision. It can take minutes to adjust properly on going from

light to dark. All these, as well as simple factors such as the distance at which a

colour is viewed and even its size and shape effect the perception of hue,

lightness and colourfulnessError: Reference source not found. They would thus

all need to be taken in to consideration when a forensic examiner assesses a

bruise as subtle changes in the perceived colour of a bruise could obviously be

confused with the subtle change in the actual colour of the bruise that could

reveal an accurate age.

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One of the most important considerations and one for which there appears to be

an almost complete lack of consideration for what is commonly called colour

blindness. It again would be better to describe such individual as having a

colour vision deficiency (CVD) as in most cases described by the general use of

the term colour blindness colour is still perceived, just in a distorted manner.

Cases of monochromacy, where colour is not perceived at all is due to

either a complete lack of functioning cones or only one functioning type

of cones, are extremely rare. More common are cases of dichromacy

where only two functioning cone types are present and anomalous

trichromacy where all three cone types are present but one of the cones is

anomalous meaning their perception of colour differs from the rest of the

population. A review of papers looking at colour vision deficiency in the

medical community by Spalding21 showed the prevalence was similar to

that of the wider population in that the most common form of colour vision

deficiency is deuteranomalous, which greatly decreases the efficiency of

discriminating between the colours that are normally perceived as red and

green as demonstrated in figure 2.6. This is present in around 5% of males with

other types “red-green” deficiencies being present in around 3% of males.

These figures are far lower for the female population at below 1% for all types of

“red-green” deficiencies. Blue-yellow deficiencies are rare but still present in

around 1 in 10 000 of the population. Spalding22 also conducted a further study

on how colour vision deficiency affects the assessment of clinical photographs

by medical professionals. This showed that examiners with CVD have inherent

difficulties in assessing certain medical conditions. It has been asserted that the

perception of reds is crucial in the assessment of bruise age it is highly unlikely

a forensic examiner with a “red-green” deficiency would be able to age a bruise

with a high degree confidence.

21 Spalding J. A. B. (1999) Colour vision deficiency in the medical profession. British Journal of General Practice, 49, 469-475.22 Campbell J.L., Spalding J. A. B., Mir F A. Birch J., (1999) Doctors and the assessment of clinical photographs — does colour blindness matter?, British Journal of General Practice, , 49, 459-461.

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Figure 2.6 Left a digital image of bruise photographed with a colour chart

present. Right the same image was processed to approximately appear

how someone with deuteranope, which causes “red-green” colour

deficiency, would perceive the colours present in the image. It is clear the

redness that would tell a FME that the bruise is relatively young is not

clear in the right hand image (This was generated online using at

www.vischeck.com), (Photo M. R. Perrett).

It is not stated in any of the studies reviewed in the present text whether the

forensic examiners partaking in them were screened for colour vision

deficiencies as there is almost a 1 in 12 possibility disregarding gender (1 in 12

in men) that any given participant will have a colour vision deficiency. The

screening processes are very simple with the use of Ishihara colour test plates

(an example of one is shown in figure 2.7) being the most common method.

There are many websites providing online colour vision deficiency tests.

However even in the population of those with normal colour vision there is

significant23 variation due to variance in the shape receptor and in the chemical

compounds they work by. There is also a natural “yellowing” of the lens with

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age24 that in an advanced form is known a cataract. While this is usually

corrected by chromatic adaption it could well have an effect on the perception of

the yellow colours which are of importance when examining bruises.

Figure 2.7 An Ishihara colour test plate to test for red-green colour

blindness. Someone with normal colour vision would see the number

“74” where as someone who was red green colour blind would not.

It is clear from the survey of the literature reported above that the human visual

system is an exceptional useful and versatile system. Many of the processes

that make it so useful are detrimental to the accurate viewing of colour that

would be needed to age a bruise to a degree of accuracy that would be

significantly valuable. It cannot be ignored though that the perception of colour

is a useful tool for the description of bruises however in order for a bruises

colour to be described in enough detail to be suitable for scientific study a

quantified colour system must be defined for use.

2.5 Basics of Colour Reproduction

It is taught from a young age that primary colours, erroneously usually said to

be red green and yellow, can be combined to make a multitude of other colours.

The confusion arises from the two ways that colours can combine. The true

primary colours are red, green and blue, which has stated above correspond

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approximately to the short, medium and long cone receptors in the eye. These

colours only work as primaries when using additive colour mixing, as shown on

the left of figure 2.8. Just as white light can be split in to the visible spectrum, in

principle red, green and blue lights can be combined (note the starting “colour is

black”) to produce the secondary colours, cyan (blue and green), magenta (red

and blue) and yellow (green and red). These colours are produced when using

equal intensities of the pure corresponding primaries; it is when equal (high)

intensities of each are combined that “white” is produced. When there are equal

intensities of each primary colour but they are not intense enough to be

perceived as white light, varying shades of greys are perceived. It is by

combining three primary colours at varying intensities that the computer monitor

that this is being typed (and maybe being read from) can display a multitude of

colours using pixels that are composed of just three different sub-pixels each

corresponding to one of the additive primaries. It is this same principle that is

used by nearly all colour devices such as televisions and data-projectors.

Figure 2.8 The left hand image demonstrates the additive principle of

colour where Red, Green and Blue light combine to form the secondary

colours Cyan, Magenta and Yellow with all three combining to make white

as primarily used in electronic displays. The right hand image shows how

the secondary colours are subtracted from white to form the primaries and

a near black as used primarily in printing.

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If however you are reading this dissertation printed on white paper a different

method is used to create the various colours seen. This is known as subtractive

mixing, which works in the opposite way to additive mixing as seen on the right

hand side of figure 2.8. When viewed under white light various wavelengths are

absorbed, or subtracted, by the inks, pigments or dyes (collectively known as

colourants) used in the printing process, to produce the array of colours

present. In the subtractive process primaries of yellow, magenta and cyan are

used however these are not ideal and so a black is used in order to produce

dark tones, this thus referred to as CMYK, (K used for black and B is used to

denote B). It is important to keep in mind that if viewed on a monitor the additive

method is also being used to display the colours shown in the example

subjective mixing and vice versa is viewing a printed copied.

2.5 Metamerism

It is this property of the visual system that allows us to effectively reproduce

colour in devices such as televisions and computer monitors using only of red,

green and blue or via CMYK printing, it is important to note that when either of

these methods is used to reproduce a colour it is only a closely matching

metameric colour that is being produced.

Figure 2.9 Metameric spectrums of light skin and foliage. The dashed

line in both graphs shows examples of the reflective properties of light

skin and foliage while the solid line shows the spectrums emitted by a

RBG phosphor CRT monitor. In both cases the widely differing

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spectrums are perceived to be the same colour. (Reproduced from

reference Error: Reference source not found page 191)

2.7 Colour matching and the CIE colorimetry system

Before the availability of spectrophotometers, methods, such as the Lovibond

Comparator and the Munsell Color System which were used to arrange colours

in a systematic manner had to rely on colour perception. However as has been

described above, these fall short, as the perceptual attributes change with

illuminant and observer. The physical properties of an object that result in colour

do not change. To over come this problem the colours need to match colours

with precision and accuracy.

As described above all colours along the visible spectrum can be matched by

combining three (practically) monochromatic lights. It is this idea, relating to the

three cone receptor types, that has been used to build what is currently the

most widely used standardised colourimetry system. This system uses colour

matching experiments in which a test field of light of wavelength λ is visually

matched by adjusting the amounts of the primary R, G and B primary lights in

an adjacent reference field. The first colour matching functions set out by the

CIE employed a 2ofield of vision that covered only the area is was believed the

foveal vision covered, these function where adopted by the CIE in 1931 and are

now know as the CIE 1931 standard observer and it is these functions that have

become the back bone of modern colourimetry. In 1964 the CIE developed

another set of functions that used a 10o standard observer, and differ from the

1931 observer.

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Figure 2.10 XYZ Colour Matching Functions of the CIE 1931 standard

observer. These are a transform of the original experimental values that

contained negative values that were not easily manipulated before

computers.

The colour matching functions showed the proportions of each of the primaries

lights used needed to match the colour perceived of light of a given wavelength

λ. It was however found that there were some colours in the spectrum that could

only be matched by adding the R primary to the test field. Because of this the

functions r(λ), g(λ) and b(λ) were transformed to the functions x(λ),

y(λ) and z(λ) (shown in figure 2.10). These are then related directly to the

spectral power distribution I(λ) by the equation 2.1.

Equation 2.1

With these equations we can calculate the X, Y and X values of any given

spectral power distribution, when these are used for some measuring

transmitted of reflective light a weighting of k is used25. Remembering that two

very different spectral power distributions these can be perceived as the same

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colour tristimulus values are how a colour is defined. However these values

need to be accompanied with information of the standard illuminant used to

measure them and the standard observer used.

Equation 2.2

The CIE system was designed so that the Y value corresponds to the

brightness or luminance of the colour. This was done so that three tristimulus

values could be reduced to two chromaticity coordinates which then be shown

on a two dimension plot. Equation 2.2 is used to achieve this. The resulting

Chromaticity Diagram (shown in figure 2.11) thus shows all the possible

chromaticities visible to the human eye.

Figure 2.11 CIE1931 xyY Chromaticity diagram for the 2oobserver

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The abstract three dimensional plot of the CIE 1931 standard observer is known

as a colour space. The colour space can be used for effectively showing the

colour gamut of a display system such as a computer monitor or printer by

plotting the points of the primaries of the device on a CIE1931 xyY chromaticity

diagram and joining them. This forms a triangle containing all the chromaticities

(at a given colour temperature for monitors) that it is possible for the device to

output. It may be a case that some of the colours that may be useful in ageing a

bruise may fall outside of the colour gamut of some imaging or reproduction

devices and this is a area that may well need a comprehensive study to

determine the reliability of such devices for use in bruise analyse.

2.8 Colour Spaces and Colour Management

Any colour space should in theory be able to be converted to any number of

other colour spaces that are of a more practical use in the field they are being

used in. Printers as explained above use a CMYK colour space. The standard

sRGB colour space was developed for the reproduction of colours on monitors

and the internet and is now used as a colour space in many digital capture

devices. Digital images should have an ICC profile ‘embedded’ or encoded in to

their metadata§. This profile allows a device to read from the image file how to

reproduce the colours of the image correctly. This is basics of the process

known as colour management, which is very important in a situation such as

analysing the colours present in a bruise as the process of managing workflow

so that any reproductions of a bruise will be as true to the original as possible.

It is important to note here that it may be the case that some colour

management systems may be optimised for the aesthetic appearance rather

than for accurate colour reproduction.

Colour management can be a very complex task when many devices such as

scanners, cameras, displays and printers are employed as each needs to be

able to know how all the other devices in the workflow have encoded the

§ Metadata is information stored in an image file that holds information about the image or file rather than the data that stores the actual image data. In an MP3 file for example the files metadata can hold the artists name and the song title.

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colours in the digital image. The most effective method of simplifying colour

management is for each device to encode the image to a device-independent

colour profiles based on colorimetric values. This enable a wide array of devices

to be able to effectively keep colours managed. If a small number of devices is

being used in a “closed loop” in that the information will stay on only the

machines in the loop then it maybe best to use device-dependent colour profiles

as that way there is less room for errors. An important area of colour

management is device characterisation, which maps the output of a device, be

an input or output device, to a set of known inputs. For example allows for two

characterised monitors showing the exact same digital image to reproduce the

same colours on the display whereas two un-characterised monitors may

display the image considerably differently.

where

Equation 2.3

An important colour space is the CIE L*a*b* space (shown in figure 2.12) which

is a transform of the XYZ colour space (equation 2.3)** that is more visually

relevant in that the component channels are arranged on an opponent axis. L*

being the brightness channel (brightness being the absolute value for lightness)

and a* and b* on a perpendicular plane with a* approximating red-green

** Xn, Yn and Zn are the CIE XYZ tristimulus values of the reference white point.

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opposition and b* approximating blue-yellow opposition. From a* and b* the hue

angle (hab) can be calculated (using equation 2.4) to define the hue. A hue angle

with +a* and +b* (0-90o) being predominantly red, a hue angle with -a* and +b*

(90o-180o) being predominantly purple, a hue angle with -a* and -b* (180o-270o)

being predominantly blue, a hue angle with +a* and -b* (270o-0o/360o) being

predominantly green.

hab = arc tan(b*/a*)

Equation 2.4

As the CIE L*a*b* space is perceptually relevant it can be used to calculate

colour differences (in there simplest form) using Euclidean geometry to give a

value ΔE*ab as a measure of visible colour difference. This a very useful tool for

measuring the error of colour reproduction. Studies that have used the CIE

L*a*b* to show the results of their assessment of skin colourError: Reference

source not found have shown that the colour of skin is far more variable on the

a* axis, than on the b* axis. As it is the ‘yellow’ biliverdin present in bruises that

the literature suggests is the best way to age a bruise, this would suggest that

b* value that is likely to vary in relation to the bruise age while the a* will only

vary with skin colour. It is for this reason this project aims to characterise the

captured images to the CIE L*a*b* colour space.

Figure 2.12 CIE L*a*b* space at three values of L*

3. Measuring the colour of bruises

3.1 Spectrophotometry

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The chemical components of a bruise have different spectral characteristics.

These can be measured by transmission spectrophotometry figure 3.1 shows

the spectra of solutions of haemoglobin, bilirubin and biliverdin measured in the

laboratory at Barts. Haemoglobin has a large absorbance peak at 414nm – its

red colour whilst bilirubin also absorbs at 390nm and at 680nm. This data

corresponds to that given in the review of LangloisError: Reference source not

found. It is normally impractical to use transmission spectrophotometry on living

or intact tissues such as a bruise.

0

0.2

0.4

0.6

0.8

1

1.2

1.4

300 400 500 600 700 800 900

Wavelength (nm)

Ab

sorb

ance

(A

U) Haemoglobin

BilirubinBiliverdin

Figure 3.1 The spectra of the haemoglobin and its breakdown products

3.2 Colourimetry using tristimulus colourimetry

A practical approach is to use reflectance spectrophotometry to measure the

reflectance spectra of a bruise. There is a tendency to confuse transmission

and reflectance colourimetry in the literature. Colourimetry is the measurement

of the spectra in the visible region. LangloisError: Reference source not found

reviewed the limited literature on the analyses of skin colour using colourimetry

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and extended this to a small number of studies on bruises. Trujillo, Vanezis and

Cermignani26 were among the first to use this technique to measure bruises.

More recently Langlois’ group27 have used a standard spectrophotometer

modified with a fibber optic cable and reflectance probe for the demonstration of

haemoglobin and its degradation in bruises.

The use of sophisticated equipment is not normally applicable in the A & E

department of a hospital, a police station or a mortuary. It would be of great

benefit if a method could be developed using more widely available and

versatile equipment, such as digital cameras. As it is already a protocol to

photograph a bruise for recording the evidence such a method would be highly

practical.

3.3 Colourimetry using digital cameras

Digital cameras work by the lens focusing light on to a photosensor array, with

each pixel element (pixel) outputting an electrical response proportional the light

incident upon it. There are several varieties of photosensor used in current

digital camera but the most common is the charge-coupled device (CCD).

These are sensitive to a wide range of wavelengths extending from the short

wavelengths of the visible spectrum into the infra-red. It is thus necessary for

the CCD array to filter the light incident upon each pixel using an infra-red filter

and a tricolour micro-filter array. The micro-filter array consist of narrowband

red, green and blue, filters usually in a 1:2:1†† ratio as in the most widely used

the Bayer filter (shown in figure 3.2).

†† A ratio of R:G:B filter of 1:2:1 is used due to the human visual system being able to discriminate more greens than other chromaticities as noticeable in the large area of the CIE xyY chromaticity diagram containing green chromaticities.

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Figure 3.2 A representation of how a Bayer filter over lies a CCD sensor

The filtered light incident on each pixel is then converted from an analogue to a

digital signal. The number of bits the signal is encoded with is known as the bit

depth. The greater the bit-depth the greater the tonal range of the image i.e.

the total possible number of tones that can be distinguished in the image. A bit

depth of 8 bits (28) or 256 levels is usually considered sufficient to give near

photographic (film) quality however a bit depth of 216 is used so that the image

can be processed further however this uses more processing power. The digital

image is then formed of a two-dimensional array of pixels holding values

between 0 and the bit depth most commonly 255 (28-1). In its raw form the

digital image is composed of pixels of values that represents levels of red,

green or blue. In digital SLR cameras it is possible to have this raw image as

the output file which is often referred to as RAW but there is not a standard

RAW file format across manufacturers. More commonly the pixel values of the

image are split in to three channels of R, G and B, in which the missing values

in the channel are calculated by interpolation. The most common file format to

store an image of this structure is the TIFF format. TIFF format is larger than the

RAW format but is a widely recognised file format that can be easily processed

and transferred.

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In computing it is desirable for files to be of as small a file size as possible in

order to take up less memory and be transferred more quickly. A common

method to achieve this is to compress the file. There are two compression

methods, lossless in which none of the information in the file is removed and so

the file size is only slightly reduced and “lossy” compression in which

sophisticated algorithms are used in order to remove extraneous information in

the image with as little perceptual effect as possible. As it has not yet been

established what is of importance in the processing of images of bruises to

extract colour information it is recommended that the images of the bruises are

stored in a lossless file format.

In order to know how a camera reproduces colour the output of the camera

needs to be related to inputs of known values, the process of doing this is called

camera characterization. This relates the cameras colour space to a device-

independent colour space such as the CIE XYZ 1931. It is an important factor

when performing camera characterization in that an auto white balancing,

where the brightest pixel is set as the white point for the image in that the

camera values R=G=B=255. The most effective method to characterize in a

camera is to use the device to image a chart of know tristimulus values,

including a set of neutral patches which can be used to linearize the camera

responses. The process of linearization then allows for the camera RGB

values(C) to be linearly related to the tristimulus values (T) by m x 3 transform

matrix A:

T=AC

Equation 3.1

As the values of T and C are known it is possible to calculate the matrix A

using:

A=D+T

Equation 3.2

The simplest transforms is when A is a 3 x 3 matrix, though more accurate

characterisation can be achieved by using polynomial transforms or artificial

neural networksError: Reference source not found.

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Aims & Objectives

The age of a bruise can often be an important factor in legal proceedings both

in terms of dating a bruise to a crime and linking a particular bruise to a specific

act of violence. Currently the age of a bruise is judged by a forensic examiner

whose expert opinion is presented and used in a court of law. However, recent

studies have shown that their assessment of bruise age is inaccurate. There is

currently no proven, objective method for approximating the age of a bruise.

Following my review of the literature relating to forensic aspects of bruises and

the related colour measuring systems the following aims were developed.

To establish a reproducible and standardised system for producing

bruises.

To establish a reproducible and effective system for the digital

photography of the bruises. To use this system to photograph the

changes in a bruise over its duration.

To produce a basic level program that can characterise a digital image

taken with unknown illumination based upon a colour chart in the image

of known tristimulus values.

To produce a program that can extract forensically useful colour

information from the colour characteristics of the bruise.

To document the need for such a program so it is understandable by

both those in the medical and imaging science fields.

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4. Methods

4.1 Apparatus

L190-GR Portable Aspirator from Life Support Products Allied Health

Products St. Louis MO 63110 USA

Canon® EOS 350D Digital SLR (8 Megapixel) un-modified

Canon® EF-S 18-55mm f/3.5-5.6 USM II Zoom Lens with no additional

filters

Two tungsten-filament studio “hot lights”

Fully extendable and adjustable tripod

BST13 small greyscale and colour separation guide‡‡

GretagMacbeth® Color-Eye 7000A Reference Spectrophotometer

Macbeth House, Pacific Road, Altrincham, Cheshire WA14 5BJ

4.2 Software

Microsoft Office® Excel 2007

Canon® Digital Photo Professional

Adobe® Photoshop® CS3

ImageJ 1.42

Mathworks MATLAB® 7.2.0.2332 (R2006a)

o OPTPROP, a colour properties toolbox by Wagberg (available at

www.mathwork.com)

o Colour Toolbox by Westland, Ripamonti that accompanies

reference Error: Reference source not found

4.3 Bruise creation

Two physically healthy adult Caucasian volunteers in early twenties consented

to being subjects for the study. Neither had any underlying illnesses which

‡‡ BST13 Purchased from ColourConfidence.com; No manufacturer details are given with the product itself or on the site though from its given Product Code: DANE001 it would suggest that it is from www.danes-picta.com. Both sites state that the BST 13 is “analogue to Kodak Q13”. This was chosen over the more widely used GretagMacbeth ColorChecker® as it was of a more reasonable price suitable size and shape to place along side the size of bruises being photographed. For details and measurements and illustration see appendix 1, 3-4.

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would have prevented them from taking part in such a study. They inflicted

bruises upon themselves using a slight modification of the method developed by

PillingError: Reference source not found. In outline bruises are inflicted by

applying suction to the skin which ruptures the underlying blood vessels in a

controlled manner.

Figure 4.1.The portable aspirator, this creates a vacuum in the reservoir

which is adjustable using the knob on the front. The vacuum itself is

gauged by the dial on the front.

A 60ml syringe barrel was attached via thick walled tubing to the vacuum tank

of the clinical aspirator shown in figure 4.1. As it is illegal under English law to

deliberately inflict a bruise on another person consenting or not, the volunteers

therefore were required to apply the vacuum themselves. The syringe was

placed on the area to be bruised and held in position by the subject (Figure 4.2).

The subject then turned on the vacuum pump in the aspirator. The pressure

was reduced to -600mmHg over five minutes by the subject turning the control

dial. Full suction was then applied for a further 10 minutes making 15 minutes in

total. This was over seen by medically trained staff in a laboratory at Bart & the

London Medical School to ensure the volunteer’s safety and that the correct

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protocol was followed. Both subjects inflicted themselves with two bruises. The

anterior aspect of the upper arm was used in three cases as this area has been

shown to bruise well using the method used and is generally of an even

pigmentation. This area is also easily to be positioned for photographing yet can

be easily concealed by clothing. One subject bruised them self on each arm

while the other subject bruised them self on the anterior of the lower right arm

as the anterior of the upper left arm was deemed unsuitable due to scarring.

Figure 4.2 Inducing a bruise: The syringe barrel is attached aspirator’s

reservoir which produces enough suction to hold the barrel in place on the arm.

The method created a bruise of approximately the same area as the cross-

section of the syringe barrel. The resulting bruise was generally circular in

nature with a diameter of approximately 3 cm with an even colouration however

this was not always the case. The method initially caused indentations due to

rim of the syringe on the skin and some redness, these were given time to fade

away before the first photographs were taken.

4.4 Image capture

This was performed in a light tight room in order that all the lighting was from

known and measurable sources. The two sources used were two 240V, 200W

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tungsten lamps and the ambient light in the room, which came from ceiling

mounted fluorescent-tubes diffused by an opaque covering typical of those

found in laboratories and examining rooms. Each bruise was photographed

under the tungsten illumination the ambient illumination and a mixture of the two

giving three combinations in total.

The camera was mounted on the tripod facing the work bench it was stood on

as shown in figure 4.3. The greyscale was stuck to the colour chart so that they

were side by side length ways. (This arrangement is referred to collectively as

the “colour chart” from here on). The colour chart was raised to be at

approximately the same height / level of the arm, and therefore the bruises,

using some black blocks that were stuck in position on the bench. The colour

chart was also arranged parallel to the image plane.

Figure 4.3 The camera and lighting set up as viewed from above.

Since it was not possible to lock the focal length of the lens the focal length was

set at one extreme of its range so that it could be kept constant. In this case the

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setting was 55 mm as it produced less noticeable distortion than the 18 mm

extreme of the lens.

Figure 4.4 A typical original image showing the relationship of the colour

chart to the bruise

The camera position and height was adjusted so that camera was parallel to the

work bench and the colour chart was fully in shot along one edge of the image

as shown in figure 4.4. In this case the camera was 50 cm from the colour chart.

The two tungsten lamps were placed either side of the camera set up and

angled down approximately 45o to the work bench and approximately 30oto the

colour chart as seen in figures 4.3 and 4.5. This gave even illumination of the

colour chart and the subject without any spectral reflection.

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Figure 4.5 The camera set up as viewed from the side.

The camera’s white-balance was set to the tungsten option, the relative ISO

was set to 100 and colour space set to sRGB and the image quality set to RAW.

A good exposure setting was then determined with an aperture setting of f/16

and the shutter speed adjusted accordingly with the camera mode dial to

manual exposure (“M”) setting so as to have complete control over these

settings. This was done with each lighting setting used until a setting was found

that gave a good coverage of the histogram. These settings were recorded and

the same settings used for each light source throughout the image capture

phase. Details are shown in appendix 6.

Each bruise was photographed daily§§ during the period that it was still visible to

the human eye. The subject was asked to place the bruised area next to the

colour scale adjusting themselves so that they were in a comfortable position

where they could remain relatively still and did not obscure the illumination, as

far as possible clothing and jewellery were kept out of the frame. The camera

§§ Weekends excluded as there was no access to the room in the university in which the apparatus had been set up.

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was then focused using the lens’ auto-focus, the colour chart having enough

detail to allow this mode to effectively work. The camera shutter was triggered

using its self-timer in order to eliminate any camera shake caused by the

manual triggering of the shutter as an electronic cable release was not at hand.

This was done under each illuminant, ensuring the correct settings and

checking the histogram to ensure images had not been under or over exposed.

A record was kept logging the details of each exposure, including the time, to

the nearest 5 minutes and the file name see appendix 7-10. Between sessions

the room was left locked so that the equipment was undisturbed. The colour

chart was covered and all lights were left off in order to decrease any

possibilities of the colour patches fading.

Figure 4.7, An image typical of those captured during the study, showing the

arrangement of the colour charts to a bruise.

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Health and Safety

The studio “hot lights” gain their name from the intense heat they

produce when left on for extended periods. Due to their low height

and being in a small confined room they were thus turned off when

not in use to minimise an accidental contact. The door was kept

open when not shooting. Due to the camera’s positioning and the

need to keep it in position it was necessary to stand on a stool in

order to view the LCD screen on its back. It was checked that the

stool used was firm and stable.

4.5 Measuring the colour chart

Each patch on the greyscale and colour chart was measured using the Color-

Eye Reference Spectrophotometer calibrated as per the manufacturer’s

instructions (see appendix 2). All patches were automatically measured three

times with the average being given as the result. The standard D65 illuminant

and a 2^ standard observer were used in measuring. The measurements are

given in appendix 3 and a measure of the variability of the colour is given in

appendix 4. For this the green patches were chosen to be measured 10 times

with the patch being moved between each measurement. This was in order to

determine if the colour of the patches were homogeneous.

4. 6 Pre-processing

The RAW .CR2 were then transferred to a consumer desktop PC running

Microsoft Windows Vista using the camera’s USB interface cable. The files

were renamed to the name format given in appendix 7-10. The filenames are a

combination of a code identifying the bruise and the light source and the age of

the bruise in hours with preceding zeros where necessary for ease of later

processing. The files were then batch processed using the Digital Photo

Professional software to convert them to Exif-TIFF 8bit files with a resolution of

350 dpi and embedding the ICC profile maintaining the image size and

filename.

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Figure 4.8, Screen shot of Photoshop CS3 showing how the images were

cropped.

The image was selected in which the bruise appeared to be the greatest

distance from the colour chart. The TIFF file of this image was then opened in

Photoshop and rotated and cropped so that the edge of the colour chart was

adjacent to left hand edge and top and bottom defined the final image. The right

hand edge was cropped as far to the right hand edge of the image as possible.

The cropped image was then saved with the same settings as the original

image. The dimensions of this image were noted and entered in the “height”

and “width” boxes that appear when the crop tool is selected.

The remaining images were then cropped so that the colour chart defined the

edges of the images as described above (as shown in figure 4.8) and the

cropped images were saved. However by having inputted the dimensions into

the Photoshop® crop tool the aspect ratio was maintained and the cropped

image resized to the same dimension as the initial image. This resulted in all the

cropped images being the exact same size with the colour chart in the same

position and orientation.

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It was these TIFF files that were used in all further image processing. For

reference these images are provided on the DVD enclosed with this

dissertation.

4.7 Processing

Due to the number of files that need to be processed which would be a time

consuming exercise it was decided to batch process the images. MATLAB was

used in order to write such a batch process. An input function was written that

the files to be processed could be selected using a GUI rather than needing to

input the files individually using written code. The structure stored the filename,

and split it in to its constituent parts, bruise code, lighting and age and a

designated bruise number. The structure also read the mean pixel values of the

greyscale and colour chart sorting them as arrays in the structure using the

readgreyscale and readclourpatches functions given in appendix 11.

These work by creating a mask that passes over each patch and records and

stores the mean pixel value of each channel in the array. These functions

required that the size of the patches in the images is known. This was manually

measured using the straight line tool found in ImageJ program.

Table 4.1 MATLAB program to input the bruise

function bruiseinput

% Inputs selected files (selected during running) in to

a structure file

% for as a pseudo database of the bruise images. Image

files selected need

% to be in the MATLAB search path.

% Opens GUI in which file(s) can be selected

filenames = uigetfile({'*.tif', 'All Files (*.tif)'},

'Pick a file', 'MultiSelect', 'on');

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% Runs if bruise structure already exists

if exist ('bruisestructure.mat','file')>0

load ('bruisestructure.mat');

n = [bruise.number];

n = max(n);

else

n=0;

bruise(n+1).filename = [];

end

nof = prod(size(filenames));

x = {bruise.filename};

for m = 1:nof;

y = strcmp(x, filenames(m));

if sum(y)==0

n = n+1;

bruise(n).filename = filenames{m};

fn = bruise(n).filename;

x{n} = filenames(m);

bruise(n).number = n;

Pixies=num2str(fn(1:3));

bruise(n).age = str2double(fn(4:8));

if strcmp(fn(3),'T')

bruise(n).lighting='Tungsten';

elseif strcmp(fn(3),'M')

bruise(n).lighting='Mixed';

else

bruise(n).lighting=unknown;

end

im = imread(fn);

im = double(im);

bruise(n).grayscale = readgreyscale(im);

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bruise(n).colourpatches = readcolourpatches(im);

end

end

save 'bruisestructure.mat' bruise

4.7.1 Camera Characterization

Characterization uses linear transforms to relate camera RGB pixel values to a

device independent colour space, in this case CIE 1931 XYZ. The structure

bruise created using bruiseinput containing the input images was inputted

in the function charbruise2Lab which linearize the bruise than then

transformed the camera RGB values to XYZ tristimulus values which where

then transformed to CIE L*a*b* values used the xyz2lab function from the

OPTIC toolbox. The values relating to the empirical measurements of the colour

chart where stored on excel tables (see appendix 3 and DVD) that where

loaded in charbruise2Lab.

4.7.2 Linearization

As characterization uses linear transforms to relate camera response to device

independent of colour spaces the first step should be to correct for any non-

linearity of the camera responses. This was achieved by using the getlincam

and lincam from the colour toolbox that accompanies Computational Colour

Science using MATLAB28.

4.7.3 Calculation of Transform

This was achieved by calculating the pseudo inverse of the 1 x 3

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Table 4.2 MATLAB program to characterise and convert the bruise images to

CIE L*a*b* values

function charcterise2Lab(bruise)

% Load file storing measured grayscale XYZ values

grayscaleXYZ = xlsread('grayscaleXYZ.xls');

% The values of Y are in the second column of the Excel

spread sheet

Y=grayscaleXYZ(:,2);

% Load file storing measured colour patch XYZ values

XYZ = xlsread('colourpatchXYZ.xls');

for n = 1:numel(bruise)

im = imread(bruise(n).filename);

im = double(im);

graycaldata = getlincam(Y',bruise(n).grayscale);

% Linearise camera output

im=lincam(graycaldata, im);

% Calculate Tranform using XYZ=T*M

% Create psuedo inverse of M (RGB values from image)

inM = pinv(bruise(n).colourpatches);

% Calculate transform T

bruise(n).transform = inM*XYZ;

% Make IM row vector for ease of matrix algebra and

apply transform

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imsize = size(im);

im = reshape(im,prod(imsize)/3,3);

im = im*bruise(n).transform;

im = reshape(im,imsize);

% Convert XYZ image to Lab and save

im = xyz2lab(im);

fn = bruise(n).filename;

fn = [fn(1:8) 'lab.mat’];

save(im, fn)

bruise(n).labfile=fn;

end

save 'bruisestructure.mat' bruise

4.8 Characterization Error

The colour differenced of the CIE L*a*b* values of the colour patches in the

characterised image and the measured CIE L*a*b* value of the colour chart

where calculated using the de function from the OPTPROT toolbox to calculate

the ΔEab colour differences between the measured L*a*b* values of the colour

chart and the characterised L*a*b* of the colour chart in each of the converted

images.

Table 4.3 Function to calculate colour characterisation error

function charerror = colcharerror(bruise)

% Load spreadsheet containing measured CIE L*a*b* values of

colour patches

ref = xlsread('colourchartLab.xls');

patch = size(ref,1);

nobrus = numel(bruise);

charerror = zeros(patch,nobrus);

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for b = 1:nobrus

im = load(bruise(b).labfile);

imlab = readcolourpatches(im);

for i = 1:18

charerror(i,b) = de(ref(i,:),imlab(i,:));

end

end

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5. Experimental and results

5.1. Bruising

Initial attempts to create a bruise using a standard household vacuum cleaner

were in part successful but the process did not appear reproducible on a daily

basis. A more reliable method was then developed on this idea by PillingError:

Reference source not found working at Barts and The London School of

Medicine. She used a medical aspirator attached to a syringe barrel that

allowed the pressure of the vacuum to be kept effectively standardised. The

bruises produced by this method were generally circular in nature and of the

same diameter though not all were totally circular with some being of a crescent

shape (as shown in figures 5.1 and 5.2).

Figure 5.1 The images of two of the bruises produced and photographed

for this study, Left image: was subject B (lower arm), right image subject

B upper arm, both taken under tungsten illumination.

There was no evidence that the site of the bruise, upper and low right arm on

one subject, upper right and upper left arm on one subject, dramatically affected

the intensity of the bruising.

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Figure 5.2 Two of the bruises produced and photographed for this study,

Left image: subject M (left arm), right image subject M right arm, both

taken under tungsten illumination.

5.2. Illuminant

At the start of these studies three sets of images under different lighting

conditions were made of every bruise. Fig 5.3 shows the same bruise taken

under ambient, photographic tungsten and a combination of ambient and

tungsten.

It was clear even with a casual visual inspection of the images that those taken

using the ambient room lighting alone suffered from spectral reflection off the

colour chart as seen in figure 5.3 (left). Therefore these ambient TIFF images

were not cropped and not used any further. The other lighting conditions did not

show any signs of spectral reflection other undesired illumination.

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Figure 5.3 Images of the same bruise and at the same time taken under

ambient lighting (left), tungsten (centre) and a combination of ambient

and tungsten (right).

5.3. Colour chart measurements.

Figure 5.4 Close up of the pale brown showing the effects of halftone

printing and brown patch. (N.B. This may not be visible on a printed

version of this work)

It was clear having received delivery of the colour charts ordered that the colour

on them was produced in the “pale” colours by halftone printing***. The

*** This is a process where lighter shades of a colour are produced by using dots

of a darker colour on a light background as commonly seen on close inspection

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resolution of the camera had significantly blurred and thus reduced this effect in

the images by taking the mean pixel value of a large area of the patches in the

processing the halftone of the colour patches should not have caused any

problem with the calculation of the colour transformation matrix. The empirical

measuring of the colour patches with the Color-Eye spectrophotometer showed

that the standard deviations of the measurements were 3.6 (pale green) and 3.6

(green). The relative standard deviation in the colorimetric measurements was

of news print.

8 Shepherd R. (2003) Simpson Forensic Medicine 12th Ed. Hodder Arnold London, UK

9 Vanezis P. (2001) Interpreting bruises at necropsy. Journal of Clinical Pathology; 54:348-355

10 Stephenson T. (1997) Ageing of bruising in children. Journal of the Royal Society of Medicine; 90:312-314

15 Jacobson R. E., Ray S. F., Attridge G. G., Axford N. R., (2000) Manual of Photography 9th Ed. Focal Press, Oxford, UK

16 Hurlbert, A.C.; Wolf, K. (2002) The contribution of local and global cone-contrasts to colour appearance: a Retinex-like model. In: Proceedings of the SPIE 2002, San Jose, CA25 Schanda J. (Ed.) (2007) Colorimetry: Understanding the CIE System, Wiley, New Jersey, USA

26 Trujillo O., Vanezis P., Cermignani M. (1995) Photometric assessment of skin colour and lightness using a tristimulus colorimeter: reliability of inter and intra-investigator observations in healthy adult volunteers. Forensic Science International; 81:1-10

27 Hughes V. K., Ellis P. S., Burt T., Langlois N. E. I., (2004) The Practical Application of Reflectance Spectrophotometry for the Demonstration of haemoglobin and it’s degradation in bruises. Journal of Clinical Pathology 54 355-359

17

? Hunt R. W. G. Reproduction of Colour (2006) 6th ed. Wiley New York

18 Berns R.S. (2003) Bilmeyer and Saltzman’s Principles of Color Technology Chapter 1 Wiley New York

19 Curcio C. A. Allen K. A., Sloan K. R., Lerea C. L., Hurley J. B., Klock I. B., Milam A. H. (1991) Distribution and morphology of human cone photoreceptors stains with anti-blue opsin. Journal of Comparative Neurology 312 610-62423 Nayatani Y.,Takahama K., Sobagaki H., (1988) Physiological causes of individual variations in color-matching functions. Color Research & Application 13, 289–297, 1988.

24 Mellerio J., (1987) Yellowing of the human lens, Vision Research 27, 1581-1587

28 Westland, S. and Ripamonti, C. (2004) Computational Colour Science Using MATLAB, Wiley New York

5 Langlois N. E. I., (2007) The Science Behond the Quest to Determine the Age of Bruises – A Review of the English Language Literature, Forensic Science Medical Pathology 3 241-251

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unexpectedly large 64% for the “pale green” patch and 74% for the “green”

patch.

5.4 Bruise changes with time

Bruises BU, BL and MR were visible for 10 days and bruise ML was visible for 7

days. A series of images were collected showing the bruises daily during this

period. Figure 5.5 shows the bruises resolving and it is clear that the colour

changes predominantly red in the first few days to yellow towards the end. The

full set up un-cropped TIFF images are on the accompanying DVD.

11 Kaczor K., Pierce M.C., Makoroff K., Corey T.S. (2006) Bruising and Physical Child Abuse. Clinical Pediatric Emergency Medicine 7, 153-160

12 Langford A., Dean J, Reed R., Holmes D., Weyers J., Jones A. (2005) Practical Skills in

Forensic Science 3rd Ed. Chap 63, Pearson Educational, Harlow, UK

14 Munang L.A., Leonard P.A., Mok J.Y. (2002) Lack of agreement on colour description between clinicians examining childhood bruising. Journal of Clinical Forensic Medicine; 9:171-4

13 Bohnert M., Baumgartner M. R., Pollak S., (2000) Spectrophotometric evaluation of the colour of intra-and subcutaneous bruises. International Journal of Legal Medicine 113 343-348

20 Fairchild M. D. (2005) Color Appearance Models, 2nd Ed., Wiley-IS&T, Chichester, UK

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1.9 hours 25.3 hours 49.2 hours 144 hours

165.5 hours 192 hours 217 hours 240 hours

Figure 5.5: The same bruise photographed under the same conditions

showing how the colour the bruise changes with time. Hours are post

bruising.

5.5 Characterisation and Error

The programming was not full function and thus figures for this are

unavailable.

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6. Discussion

It had been intended at the start of this project that the main focus would be on

the processing of images produced by GrossmanError: Reference source not

found whose project ran concurrently with this project. In this respect Grossman

would have been covering the medical aspects such as the infliction of a

relatively large number of bruises and recording, while this project would have

covered the characterisation of the images produced and experimenting with

methods to exact colour information from the images.

However the images produced in the Grossman study were found to be

unsuitable for further processing due mainly to the poor reproduction of the

colours of the colour chart. It was thus required of the present to capture a set

of suitable images to process for the present project. With the time restraints

inherent with working on a university project this resulted in there being far less

time available to research and program a suitable and effective characterisation

process. This delay resulted in the project being forced to finish before its

desired end result of a method to segment the bruise from the captured images

from which colour information. It was immediately evident that the scope of the

project, particularly the digital processing was much larger than could be

covered in an undergraduate final year project.

However significant understandings of the problems associated with the reliable

production and processing of images of bruises have been achieved. The

importance of the correct lighting and positioning of a suitable colour chart in the

image have been researched and documented. It was shown that to avoid

spectral reflection from a glossy colour chart and the subject’s skin it was

essential to use angled lighting. Others have observed similar problems with

lighting affects and have investigated alternative light sources. Hughes et al29

used a forensic polilight® to illuminate bruises for digital imaging but found this

29 Hughes V.K., Ellis P.S., Langlois N.E.I. (2006) Alternative light source (polilight®) illumination with digital image analysis does not assist in determining the age of busies. Forensic Science International 158, 104-107

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light source was unable to assist in the ageing of a bruise. Both PillingError:

Reference source not found and GrossmanError: Reference source not found

used a ring flash and found this resulted in undesirable lighting effects such a

spectral reflection and unreliable exposure control. Langlois and Gresham30

commented that uneven lighting in their photographs prevented their objective

assessment of bruises.

Most literature studied did not mention the use of any form of colour control in

the images of bruises being assessed from photographs. Munang et alError:

Reference source not found had used an unspecified colour scale to aide the

colour reproduction images captured on colour film. Whereas the detailed

survey by Dimitrova et alError: Reference source not found does not mention

any form of colour control. Grossman used a colour and grey scale but was

unable to uses these for effective colour standardisation when using

Photoshop® to investigate bruise colour changes with age.

Given the generation of satisfactory images it will be necessary to characterise

the images so that the colour changes in the bruise with age can be

determined. In order to do this an affective method to characterise the colours in

the images need to be developed; whether imaging the bruises with a

characterised system or the images are able to be characterised individually

due to the presence of a colour chart or known values. Having characterised the

image, an effective method to extract the colours of the bruise from that of the

normal skin needs to be implemented. The extracted colour information relating

to the haemoglobin and it breakdown products would then need analysing to

detect any trends in their relationship to bruise age. A relationship may be only

between the age and yellow present in a bruise as suggested by LangloisError:

Reference source not found, or the ratio of colours relating to the degradation of

haemoglobin or a more complex function.

Each area that needs investigation in order to produce an effective system to

date bruise by digital imaging could individually have produced several

30 Langlois N.E.I., Gresham G.A. (1991). The ageing of bruises: A review and study of the colour changes with time. Forensic Science International 50, 227-238

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interesting projects. Affective characterisation methods for digital cameras are

currently still a very active area of research31,32. There is also a great deal of

research in to the assessment by digital imaging of human skin tone

Martinkauppi33 has prepared an entire doctoral thesis on the assessment of

human skin tone (of the face) alone. While most of this research is the area is

for commercial purposes such as for aiding of online cosmetic sales and the

development of computer graphics the methods developed in such studies

31 Barnard K., Funt B. (2002) Camera Characterization for Color Research, COLOR research and application, 27, 152–163

32 Liu Y., Yu, H., Shi J. (2008) Camera characterization using back-propagation artificial neutral network based on Munsell system Procedigns SPIE, Vol. 6621, 66210A doi:10.1117/12.790592

33 Martinkauppi, B, (2002) Face colour under varying illumination - analysis and applications, Ph.D. Thesis University of Oulu, Finland

Appendices

Appendix 1 Colour Chart

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could be invaluable to any future research in the computerised assessment of

bruising.

In the best case scenario where by chance this project had resulted in a method

to extract and analyse the colour information of the bruises available in the

study they would only have been from a very small control group and from

bruises caused by one type of trauma on one area of the body. As stated at the

vary start there are numerous factors that effect and could thus be relevant to

BST13 small greyscale and colour separation guide. Each card measures

60mm x 203mm. The grey scale: 20 steps, 10x22mm each. 20 steps are stated

as being in 0.10 density increments between 0.05 [white] and 1.95 (a practical

printing black) of density (from www.colourconfidence.com)

Appendix 2

Calibrating the Spectrophotometer

The Color-Eye 7000A spectrophotometer needs to be calibrated with the white ceramic calibration tile provided with the unit. It is best to calibrate the instrument at the location it is to be used. This will accommodate ambient temperature changes.

Before you calibrate…Please note the following before you calibrate the spectrophotometer:

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developing a system that could estimate the age of any given bruise to a time

frame that could stand up to the rigorous scrutiny it would face when being used

as evidence in a court of law. As this would be the ultimate goal in this area of

research.

Conclusions

Calibration is required every 8 hours. It is a good practice to calibrate hourly.

If the instrument is exposed to rapid changes in ambient temperature, calibrate to accommodate for these changes.

Make certain that the serial number on the White Ceramic Calibration Tile is the same as the serial number on the instrument. Do not substitute another calibration tile for the one originally supplied.

If the tile should be broken or become damaged, call X-Rite for advice on how to replace it.

Reflectance Calibration Procedure1. Touch and release Cell 5 on the Main Menu Display until the desired

specular component status (SCE/SCI) is displayed.2. Select the desired sampling aperture. Refer to “Changing the Sampling

Aperture” later in this section.3. Use the software program to select reflectance mode.4. Place the Zero Calibration Standard facing the unit so that it completely

covers the viewport opening.5. Use the software program to initiate the zero (black) calibration.6. Place the White Calibration Tile facing the unit so that it completely

covers the viewport opening.7. Use the software program to initiate the white tile calibration.8. After calibration return the white calibration tile to it storage area.

Source Color-Eye 7000A manualAppendix 3Colour chart readingsGrey scale

NameX Y Z xyL* a* b* A.180.1084.6690.330.310.3393.74-0.721.281.168.4272.0875.390.320.3388.01-0.212.392.155.9258.9762.790.310.3381.27-

0.331.243.144.6646.9150.360.310.3374.130.200.734.134.8036.5139.520.310.3366.910.340.285.128.7530.2332.940.310.3361.850.07-0.046.122.9324.1126.590.310.3356.200.07-

0.54M.118.8719.8722.210.310.3351.69-0.10-1.028.115.2816.1018.100.310.3347.11-0.16-1.159.112.6013.2514.790.310.3343.140.02-0.8410.110.5511.1212.530.310.3339.78-0.09-

1.1111.18.709.1910.220.310.3336.34-0.23-0.6612.17.047.428.280.310.3332.75-0.10-0.6813.15.876.166.980.310.3229.800.25-1.0714.15.095.326.130.310.3227.640.39-1.4315.14.494.685.380.310.3225.810.47-1.30B.13.914.104.760.310.3224.010.11-

1.5017.13.793.984.480.310.3223.590.25-0.8118.13.733.904.350.310.3323.350.35-0.5119.13.783.964.390.310.3323.530.31-0.43

Colour Patches

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Martin R. Perrett BSc Photographic Science and Digital Imaging

In reality forensic medical examiners will continue to use the methods they

already use. Photographs will be taken with the facilities at hand on a wide

range of camera types and under a wide variety of unknown illuminants. It is

standard practice to incorporate a measurement scale in these images and it

would only require the inclusion of a suitable colour scale in order for the image

to be suitable to process and extract the information needed to accurately age a

bruise.

NameX Y Z L* a* b* Grey50.5652.4863.4477.571.84-5.72Pale Brown44.5745.5245.4473.233.814.40White83.0986.12103.5494.372.37-6.39Pale

Magenta67.4363.1179.5583.5017.06-8.58Pale Red60.5958.8449.1781.2011.3314.15Pale Yellow76.5682.4867.0792.79-3.7017.39Pale Green54.6262.1259.3682.98-10.937.27Pale

Cyan62.2766.8995.1885.45-3.02-16.32Pale Blue50.7449.3272.9775.6510.57-17.01Black7.157.387.5332.661.361.80Brown7.597.987.9133.930.072.65White284.7387.65106.

7795.012.72-7.30Magenta34.7719.2822.2051.0268.72-2.17Red31.2918.937.1650.6158.1434.11Yellow66.9575.2412.5489.51-

9.8984.61Green11.6121.6112.3953.61-51.9423.10Cyan20.4826.1172.9358.14-19.81-47.15Blue10.438.0522.4334.0923.41-31.75Appendix 4

Reproducibility data

NameX Y Z L* a* b* ΔE*abPale Green54.6262.1259.3682.98-10.937.271.01Pale Green 256.1763.6061.4283.76-10.396.750.08Pale Green 356.5163.9361.6783.93-10.296.810.25Pale

Green 357.3864.8063.0584.38-10.086.360.86Pale Green 456.1463.5661.1983.74-10.46.920.12Pale Green 556.8764.2962.1384.12-10.226.730.45Pale Green

657.2064.6162.8384.28-10.116.40.76Pale Green 757.3464.7462.9584.35-10.076.410.82Pale Green 855.5463.0060.8283.44-10.626.740.35Pale Green 954.4361.9658.8982.89-

11.047.551.28Pale Green 1055.1362.6060.2283.23-10.736.920.59Mean56.1263.5661.3283.74-10.446.810.60Standard Deviation1.071.031.410.540.340.360.38Relative Std Dev

(%)1.901.622.300.643.275.3664.27Min54.4361.9658.8982.89-11.046.360.08Max57.3864.8063.0584.38-

10.077.551.28Range2.952.844.161.490.971.191.19Green11.6121.6112.3953.61-51.9423.10.42Green 211.6021.5912.3953.59-51.9523.080.41Green 311.5521.5512.3153.55-

52.1123.210.21Green 411.1521.1211.6153.08-53.0324.281.28Green 511.4721.4312.2553.42-52.1223.130.23Green 611.1821.1411.7053.1-52.8824.071.03Green 711.3921.3412.2553.32-

52.2522.950.40Green 811.5821.5812.3553.58-52.0223.170.31Green 911.4821.4412.2653.43-52.1323.110.25Green 1011.6121.6112.3553.61-51.9623.20.36Mean11.4621.4412.1853.43-

52.2423.330.49Standard Deviation0.170.190.290.200.390.450.36Relative Std Dev (%)1.520.872.350.38-0.751.9574.37Min11.1521.1211.6153.08-

53.0322.950.21Max11.6121.6112.3953.61-51.9424.281.28Range0.470.490.780.531.091.331.07

Appendix 5 Bruise infliction times

Bruise CodeDate Time*BU05/05/200914:00BL05/05/200914:45MR05/05/200915:00ML05/05/200914:15* Time

suction was removed

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It is hoped that this project has extensively covered all the areas needed to

achieve this goal in a clear manner that is useful to both medical researchers

and those in the image processing field who may carry on this work and will find

this a good foundation to build on. In

Appendix 6

Camera Settings

ISO: 100

Aperture: f/16

Shutter speed: 1/10 sec. for tungsten and mixed lighting1 sec for ambient lighting

Appendix 7

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References

Times and dates of photographs of bruise BL

LightingDateIMG #TimeAge (hr)New File Namen/a05/05/2009n/a14:450Tungsten05/05/20092316:401.9BLT001.9Tungsten06/05/2009

2716:0025.3BLT025.3Tungsten07/05/20094915:5549.2BLT049.2Tungsten11/05/20097113:55143.2BLT143.2Tungsten12/05/20099112:20167.5BLT167.5Tungsten13/05/20099415:10192.4BLT192.4Tungsten14/05/200910016:00217.3BLT217.3Tungsten15/05/200910615:15240.5BLT240.5Ambient06/05/20093416:0025.3BLA025.3Ambient07/05/20095015:5549.2BLA049.2Ambient11/05/20097514:00143.3BLA143.3Ambient12/05/20098612:15167.5BLA167.5Mixed06/05/

20092816:0025.3BLM025.3Mixed07/05/20094615:5549.2BLM049.2Mixed11/05/20097314:00143.3BLM143.3Mixed12/05/20098812:15167.5BLM167.5Mixed13/05/20099215:05192.3BLM

192.3Mixed14/05/200910216:00217.3BLM217.3Mixed15/05/200910415:10240.4BLM240.4

Appendix 8

Times and dates of photographs of bruise BU

LightingDateIMG #TimeDaysAge (hr)New File Namen/a05/05/2009n/a14:4500Tungsten05/05/20092416:4001.9BUT001.9Tungsten06/05/20093016:00125.3BUT025.3Tungsten07/05/20094815:55249.2BUT049.2Tungsten11/05/200972

13:556143.9BUT143.9Tungsten12/05/20099012:207165.6BUT165.6Tungsten13/05/20099515:108191.6BUT191.6Tungsten14/05/200910116:009217.3BUT217.3Tungsten15/05/200910715:1010240.4BUT240.4Mixed06/05/20092916:00125.3BUM025.3Mixed07/05/20094715:55249.2BUM049.2Mixed11/05/20097414:006143.3BUM143.3Mixed12/05/20098912:157166.0BUM166.0Mixed13/05/20099315:058191.7BUM191.7Mixed14/05/200910316:009217.3BUM217.3Mixed15/05/200910515:1010240.4BUM240.4Ambient06/05/20093516:05125.3BUA025.3Ambient07/05/20095115:55249.2BUA049.2Ambient11/05/20097614:006143.3BUA143.3Ambient12

/05/20098712:157166.0BUA166.0

Appendix 9

Times and dates of photographs of bruise ML

LightingDateIMG #TimeAge (hr)New File Namen/a05/05/2009n/a14:450 Tungsten05/05/20092616:452.0MLT002.0Tungsten06/05/20094216:1025.4MLT025.4Tungsten07/05/20095816:0549.3MLT049.3Tungsten08/05/20096513:4070.9MLT070.9Tungsten11/05/20097013:5594.0MLT094.0Tungsten12/05/20098211:40164.9MLT164.9Mixed06/05/20094016:1025.4MLM025.4Mixed07/05/20095516:0049.3MLM049.3

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Martin R. Perrett BSc Photographic Science and Digital Imaging

Mixed08/05/20096313:3570.8MLM070.8Mixed11/05/20096813:5594.0MLM094.0Mixed12/05/20097911:35164.8MLM164.8Ambient06/05/20093816:1025.4MLA025.4Ambient07/05/20095316:0049.3MLA049.3Ambient08/05/20096113:3570.8MLA070.8Ambient11/05/20096613:5

089.0MLA089.0Ambient12/05/20097711:35164.8MLA164.8

Appendix 10

Times and dates of photographs of bruise MR

LightingDateIMG #TimeAge (hr)New File Namen/a05/05/2009n/a15:000Tungsten05/05/20092516:451.8MRT001.8Tungsten06/05/200

94116:1025.2MRT025.2Tungsten07/05/20095616:0049.0MRT049.0Tungsten08/05/20096413:4070.7MRT070.7Tungsten11/05/20097013:55142.9MRT142.9Tungsten12/05/20098311:40164.7MRT164.7Tungsten13/05/20099615:40192.7MRT192.7Tungsten14/05/20099916:00217.0

MRT217.0Tungsten15/05/200910815:10240.2MRT240.2Mixed06/05/20093916:1025.2MRM025.2Mixed07/05/20095416:0049.0MRM049.0Mixed08/05/20096213:3570.6MRM070.6Mixed11/05/20096913:55142.9MRM142.9Mixed12/05/20098111:40164.7MRM164.7Mixed13/05/2

0099715:40192.7MRM192.7Mixed14/05/20099815:55216.9MRM216.9Mixed15/05/200910915:10240.2MRM240.2Ambient06/05/20093716:0525.1MRA025.1Ambient07/05/20095216:0049.0MRA049.0Ambient08/05/20096013:3570.6MRA070.6Ambient11/05/20096713:50142.8MR

A142.8Ambient12/05/20098411:45164.8MRA164.8

Appendix 11

Functions for the extraction of data from grey scale and colour chart

function [readings]=readgrayscale (im)

% Produces a 3 by 20 array of the RGB triplets of the mean pixel value of% a section of the grayscale patchs in the image. readings(:,1) storing the% value for the bottom patch inthe chart.

im=double(im);

% Manually meausered width and height of the patches in image pw=366;

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ph=155;

% mh and mw are the width and height of the area of the patch that is% measured these being 80% of the measured patch width and height to allow% for an error in the cropping to be missed.mh=round(0.8*ph);mw=round(0.8*pw);

or=round(0.1*ph);oc=round(0.1*pw);oc2=oc+mw;

readings=zeros(3,19);

for chan=1:3 for p=0:19 a=or+ph*p; b=a+mh; readings(chan,20-p)=mean(mean(im(a:b,oc:oc2,chan))); end end

function [readings] = readcolourpatches(im) % Produces a 3 by 20 array of the RGB triplets of the mean pixel value of% a section of the grayscale patchs in the image. readings(:,1) storing the% value for the bottom patch inthe chart.

im=double(im);

% Manually meausered width and height of the patches in image pw=260; ph=348;

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% mh and mw are the width and height of the area, centered on the patch, that is% measured these being 80% of the measured patch width and height to allow% for an error in the cropping to be missed.mh=round(0.8*ph);mw=round(0.8*pw);

or=round(0.1*ph);oc=round(0.1*pw)+366; % 366 is width of gray scale

readings=zeros(18,3);

for chan= 1:3 for c=0:1; for r=1:9; ra=or+ph*(r-1); rb=ra+mh; ca=oc+pw*(c); cb=ca+mw; patch = im(ra:rb,ca:cb,:); readings(r+9*c,chan) = mean(mean(patch(:,:,chan))); end endend

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