fingerprint matching by ai

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Introduction

Fingerprint matching is one of the most popular and reliable biometric techniques used in automatic personal identification. There are two main applications involving fingerprints: fingerprint verification and fingerprint identification. While the goal of fingerprint verification is to verify the identity of a person, the goal of fingerprint identification is to establish the identity of a person. Specifically, fingerprint identification involves matching a query fingerprint against a fingerprint database to establish the identity of an individual. Forensic science is the application of a broad spectrum of sciences to answer questions of interest to the legal system. This may be in relation to a crime or to a civil action. Some forensic scientists search for and examine traces of material which might either establish or exclude an association between a suspect and a victim or a crime. These traces might include: blood, saliva, semen and other body fluids, paint, glass, footwear and tyre impressions, flammable substances and explosives, hairs, fibres and vegetable material. Others analyse drugs, specimens of tissue for poisons and blood or urine for alcohol. Forensic scientists also examine firearms and documents and investigate the causes of fires, explosions and road accidents.

Fingerprint Identification

Fingerprint Identification is the method of identification using the impressions made by the

minute ridge formations or patterns found on the fingertips. No two persons have exactly the

same arrangement of ridge patterns, and the patterns of any one individual remain unchanged

throughout life. Fingerprints offer an infallible means of personal identification. Other personal

characteristics may change, but fingerprints do not.

Fingerprints can be recorded on a standard fingerprint card or can be recorded digitally and

transmitted electronically to the FBI for comparison. By comparing fingerprints at the scene of a

crime with the fingerprint record of suspected persons, officials can establish absolute proof of

the presence or identity of a person

Identification by fingerprints relies on pattern matching followed by the detection of certain

ridge characteristics, also so known as Galton details, points of identity, or minutiae, and the

comparison of the relative positions of these minutiae points with a reference print, usually an

inked impression of a suspect's print. There are three basic ridge characteristics, the ridge ending,

the bifurcation and the dot (or island).

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Island Dot Bifurcation Ending Ridge

Identification points consist of bifurcations, ending ridges, dots, ridges and islands. A single

rolled fingerprint may have as many as 100 or more identification points that can be used for

identification purposes. There is no exact size requirement as the number of points found on a

fingerprint impression depend on the location of the print. As an example the area immediately

surrounding a delta will probably contain more points per square millimetre than the area near

the tip of the finger which tends to not have that many points.

In image 1 we see part of a fully rolled fingerprint. Notice that the edges are cut-off so you can

safely assume that this is not a fully rolled impression. If you take a look at image 2 you can see

that I have sectioned out the centre portion of this impression and labelled 10 points of

identification. That was not all the points found but simply the ones that could be mapped easily

without cluttering up the image

Image 2 when measured 1:1 is just over 1/4" square. If you look closely you should be able to

identify 10 additional points that were not mapped with the lines. In all I counted 22 points of

identification on this 1/4" square section of the impression. One thing to note here, you might be

under the impression that making a fingerprint comparison is relatively easy but you should keep

in mind a couple things.

First, image 1 and image 2 are both taken from the same image. In real life you would have

impressions made at separate times and subject to different pressure distortions. Secondly, these

images are relatively clean and clear where many of the actually crime scene prints are anything

but clear. Last you have to consider that this is an easy comparison because you are blessed with

having a core pattern and a delta when in some cases you may have a latent that could be a

fingertip, palm or even foot impression.ng a fingerprint comparison is relatively easy but you

should keep in mind a couple things


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History

The first year for the first known systematic use of fingerprint identification began in the United

States is 1902. The New York Civil Service Commission established the practice of

fingerprinting applicants to pre-vent them from having better qualified persons take their tests for

them. The New York state prison system began to use fingerprints for the identification of

criminals in 1903.

In 1924 the Identification Division of the Federal Bureau of Investigation (FBI) was

established to pro-vide one central repository of fingerprints. When the Identification Division

was established its purpose was to provide a central repository of criminal identification data for

law enforcement agencies throughout the Nation. However, in 1933 the United States Civil

Service Commission (now known as the Office of Personnel Management) turned the

fingerprints of more that 140, 000 Government employees and applicants over to the FBI.

Therefore, a Civil Identification Section was established. These innovations marked the initiation

of the FBI's Civil File which was destined to dwarf the criminal files in size. In 1992 the

Identification Division was re-established as the Criminal Justice Information Services Division

(CJIS).

Fingerprint Pattern Type


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The New Age of Electronic Fingerprint Identification

Fingerprints are now processed through the Integrated Automated Fingerprint Identification

System. The fingerprints are submitted electronically or by mail, processed on IAFIS, and a

response is returned to the contributing agency within two hours or less for electronic criminal

fingerprint submissions and twenty-four hours or less for electronic civil fingerprint submissions.

Fingerprint processing has been reduced from weeks and months to hours and minutes with

IAFIS.

Fingerprint capture

Livescan devices

Fingerprint image acquisition is considered the most critical step of an automated fingerprint

authentication system, as it determines the final fingerprint image quality, which has drastic effects on the

overall system performance. There are different types of fingerprint readers on the market, but the basic

idea behind each capture approach is to measure in some way the physical difference between ridges and

valleys. All the proposed methods can be grouped in two major families: solid-state fingerprint readers


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and optical fingerprint readers. The procedure for capturing a fingerprint using a sensor consists of rolling

or touching with the finger onto a sensing area, which according to the physical principle in use

(capacitive, optical, thermal, etc.) captures the difference between valleys and ridges. When a finger

touches or rolls onto a surface, the elastic skin deforms. The quantity and direction of the pressure applied

by the user, the skin conditions and the projection of an irregular 3D object (the finger) onto a 2D flat

plane introduce distortions, noise and inconsistencies in the captured fingerprint image. These problems

result in inconsistent, irreproducible and non-uniform contacts and, during each acquisition, their effects

on the same fingerprint results are different and uncontrollable. The representation of the same fingerprint

changes every time the finger is placed on the sensor platen, increasing the complexity of the fingerprint

matching, impairing the system performance, and consequently limiting the widespread use of this

biometric technology.

Print types

Latent prints

Although the word latent means hidden or invisible, in modern usage for forensic science the term latent prints means any chance or accidental impression left by friction ridge skin on a surface, regardless of whether it is visible or invisible at the time of deposition. Electronic, chemical and physical processing techniques permit visualization of invisible latent print residue whether they are from natural secretions of the eccrine glands present on friction ridge skin (which produce palmar sweats, consisting primarily of water with various salts and organic compounds in solution), or whether the impression is in a contaminant such as motor oil, blood, paint, ink, etc.

Latent prints may exhibit only a small portion of the surface of the finger and may be smudged, distorted,

or both, depending on how they were deposited. For these reasons, latent prints are an “inevitable source

of error in making comparisons,” as they generally “contain less clarity, less content, and less undistorted

information than a fingerprint taken under controlled conditions, and much, much less detail compared to

the actual patterns of ridges and grooves of a finger.

Patent prints

These are friction ridge impressions of unknown origin which are obvious to the human eye and are

caused by a transfer of foreign material on the finger, onto a surface. Because they are already visible they

need no enhancement, and are generally photographed instead of being lifted in the same manner as latent

prints. Finger deposits can include materials such as ink, dirt, or blood onto a surface.


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Plastic prints

A plastic print is a friction ridge impression from a finger or palm (or toe/foot) deposited in a material that

retains the shape of the ridge detail. Commonly encountered examples are melted candle wax, putty

removed from the perimeter of window panes and thick grease deposits on car parts. Such prints are

already visible and need no enhancement, but investigators must not overlook the potential that invisible

latent prints deposited by accomplices may also be on such surfaces. After photographically recording

such prints, attempts should be made to develop other non-plastic impressions deposited at natural

finger/palm secretions (eccrine gland secretions) or contaminates.

Fingerprint identification method

Two approaches will be described in this project for fingerprint recognition:

• Approach 1: Based on minutiae located in a fingerprint

• Approach 2: Based on frequency content and ridge orientation of a fingerprint

First Approach

Most automatic systems for fingerprint comparison are based on minutiae matching Minutiae are local discontinuities in the fingerprint pattern. A total of 150 different minutiae types have been identified. In practice only ridge ending and ridge bifurcation minutiae types are used in fingerprint recognition. Examples of minutiae are shown in figure 1.

Figure 1. (a) Different minutiae types, (b) Ridge ending & Bifurcation


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Many known algorithms have been developed for minutiae extraction based on orientation and gradients of the orientation fields of the ridges . In this project we will adopt the method used by Leung where minutiae are extracted using feed forward artificial neural networks. The building blocks of a fingerprint recognition system are:

Figure 2. Fingerprint recognition system

a) Image Acquisition A number of methods are used to acquire fingerprints. Among them, the inked impression method remains the most popular one. Inkless fingerprint scanners are also present eliminating the intermediate digitization process. Fingerprint quality is very important since it affects directly the minutiae extraction algorithm. Two types of degradation usually affect fingerprint images: 1) the ridge lines are not strictly continuous since they sometimes include small breaks (gaps); 2) parallel ridge lines are not always well separated due to the presence of cluttering noise. The resolution of the scanned fingerprints must be 500 dpi while the size is 300x300.

b) Edge Detection An edge is the boundary between two regions with relatively distinct gray level properties. The idea underlying most edge-detection techniques is on the computation of a local derivative operator such as ‘Roberts’, ‘Prewitt’ or ‘Sobel’ operators. In practice, the set of pixels obtained from the edge detection algorithm seldom characterizes a boundary completely because of noise, breaks in the boundary and other effects that introduce spurious intensity discontinuities. Thus, edge detection algorithms typically are followed by linking and other boundary detection procedures designed toassemble edge pixels into meaningful boundaries.

c) Thinning An important approach to representing the structural shape of a plane region is to reduce it to a graph. This reduction may be accomplished by obtaining the skeleton of the region via thinning (also called skeletonizing) algorithm. The thinning algorithm while deleting unwanted edge points should not: • Remove end points. • Break connectedness • Cause excessive erosion of the region

d) Feature Extraction Extraction of appropriate features is one of the most important tasks for a recognition system. The feature extraction method used in [1] will be explained below. A multilayer perceptron (MLP) of three layers is trained to detect the minutiae in the thinned fingerprint image of size 300x300. The first layer of the network has nine neurons associated with the components of the input vector. The hidden layer has five neurons and the output layer has one neuron. The network is trained to output a “1” when the input window in centered on a


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minutiae and a “0” when it is not. Figure 3 shows the initial training patterns which are composed of 16 samples of bifurcations in eight different orientations and 36 samples of non-bifurcations. The networking will be trained using: • The back propagation algorithm with momentum and learning rate of 0.3. • The Al-Alaoui back propagation algorithm. State the number of epochs needed for convergence as well as the training time for the two methods. Once the network is trained, the next step is to input the prototype fingerprint images to extract the minutiae. The fingerprint image is scanned using a 3x3 window given

(a) (b) (c) (d) Figure 4. Core points on different fingerprint patterns. (a) tented arch, (b) right loop, (c) left loop, (d) whorl

e) Classifier After scanning the entire fingerprint image, the resulting output is a binary image revealing the location of minutiae. In order to prevent any falsely reported output and select “significant” minutiae, two more rules are added to enhance the robustness of the algorithm: 1) At those potential minutiae detected points, we re-examine them by increasing the window size by 5x5 and scanning the output image. 2) If two or more minutiae are to close together (few pixels away) we ignore all of them. To insure translation, rotation and scale-invariance, the following operations will be performed: • The Euclidean distance d(i) from each minutiae detected point to the center is calculated. The referencing of the distance data to the center point guarantees the property of positional invariance. • The data will be sorted in ascending order from d(0) to d(N), where N is the number of detected minutiae points, assuring rotational invariance. • The data is then normalized to unity by shortest distance d (0), i.e: dnorm(i) = d(0)/d(i); This will assure scale invariance property. In the algorithm described above, the center of the fingerprint image was used to calculate the Euclidean distance between the center and the feature point. Usually, the center or reference point of the fingerprint image is what is called the “core” point. A core point, is located at the approximate center, is defined as the topmost point on the innermost upwardly curving ridgeline. The human fingerprint is comprised of various types of ridge patterns, traditionally classified according to the decades-old Henry system: left loop, right loop, arch, whorl, and tented arch. Loops make up nearly 2/3 of all fingerprints, whorls are nearly 1/3, and perhaps 5-


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10% are arches. Figure 4 shows some fingerprint patterns with the core point is marked. Many singularity points detection algorithms were investigated to locate core points, among them the famous “Poincaré” index method [4-5] and the one described in. For simplicity we will assume that the core point is located at the center of the fingerprint image. After extracting the location of the minutiae for the prototype fingerprint images, the calculated distances will be stored in the database along with the ID or name of the person to whom each fingerprint belongs. The last phase is the verification phase where testing fingerprint image: 1) is inputted to the system 2) minutiae are extracted 3) Minutiae matching: comparing the distances extracted minutiae to the one stored in the database 4) Identify the person State the results obtained (i.e: recognition rate).

Second Approach Most methods for fingerprint identification use minutiae as the fingerprint features. For small scale fingerprint recognition system, it would not be efficient to undergo all the preprocessing steps (edge detection, smoothing, thinning ..etc), instead Gabor filters will be used to extract features directly from the gray level fingerprint as shown figure 5. No preprocessing stage is needed before extracting the features .

Figure 5. Building blocks for the 2nd approach

a) Image Acquisition The procedure is the same explained in the 1st approach.

b) Feature Extractor Gabor filter based features have been successfully and widely applied to face recognition, pattern recognition and fingerprint enhancement. The family of 2-D Gabor filters was originally presented by Daugman (1980) as a framework for understanding the orientation and spatial frequency selectivity properties of the filter. Daugman mathematically elaborated further his work in . In a local neighborhood the gray levels along the parallel ridges and valleys exhibit some ideal sinusoidal shaped plane waves associated with some noise as shown in figure 6 .


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Figure 6. Sinusoidal plane wave

The general formula of the Gabor filter is defined by:

Figure 6. Sinusoidal plane wave

The general formula of the Gabor filter is defined by:

The next step is to specify the values of the filter’s parameters; the frequency is cal Equation (1) can be written in the complex form giving:


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Figure 7 shows the filter response in spatial and frequency domain for a zero orientation.

Figure 7. Gabor filter response Table 1 extracted from [8] described the filter properties in space and spectral domains.

The fingerprint print image will be scanned by a 8x8 window; for each block the magnitude of the Gabor filter is extracted with different values of m (m = 4 and m = 8). The features extracted (new reduced size image) will be used as the input to the classifier.

b) Classifier The classifier is based on the k-nearest neighborhood algorithm KNN. “Training” of the KNN consists simply of collecting k images per individual as the training set. The remaining images consists the testing set. The classifier finds the k points in the training set that are the closest to x (relative to the Euclidean distance) and assigns x the label shared by the majority of these k nearest neighbors. Note that k is a parameter of the classifier; it is typically set to an odd value in order to prevent ties. Figure 8 shows how the KNN algorithm works for a two class problem. The KNN query starts at the test point x and grows a spherical region until it encloses k training samples, and it labels the test point by a majority vote of these samples. In this k = 5 case, the test point x would be labeled in the category of the red points .


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Figure 8. The KNN algorithm

The last phase is the verification phase where the testing fingerprint image: 1) is inputted to the system 2) magnitude features are extracted 3) perform the KNN algorithm 4) Identify the person State the recognition rate obtained.

c) Suggested enhancement In order to enhance the performance of the 2nd approach below is a list of proposed ideas: • Instead of using only the magnitude Gabor filter features, try to use also the phase of the filter . • Try to use the Mahalanobis distance given by: ) ( ) ( 1 m x C m x D T - - = - where m is the mean and C is the covariance matrix. Appendix A provides an example of Mahalanobis distance. • Try to other classifiers such as back propagation and ALBP. Indicate the number of layers used as well as the number of neurons. • The Gabor filter assumes a sinusoidal plane wave which is not always the case as depicted in figure 9. Try to use the modified Gabor filter described in . Figure


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Figure 9. A fingerprint with corresponding ridges and valleys.

Validity of fingerprinting as an identification method

The validity of forensic fingerprint evidence has recently been challenged by academics, judges and the

media. While fingerprint identification was an improvement over earlier anthropometric systems, the

subjective nature of matching, along with the relatively high error rate of matches when compared to

DNA, has made this forensic practice controversial.

Criticism

The words "Reliability" and "Validity" have specific meanings to the scientific community. Reliability

means successive tests bring the same results. Validity means that the results accurately reflect the

external criteria being measured.

Despite the absence of objective standards, scientific validation, and adequate statistical studies, a natural

question to ask is how well fingerprint examiners actually perform. Proficiency tests do not validate a

procedure per se, but they can provide some insight into error rates.

Defense

Fingerprints collected at a crime scene, or on items of evidence from a crime, can be used in forensic

science to identify suspects, victims and other persons who touched a surface. Fingerprint identification


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emerged as an important system within police agencies in the late 19th century, when it replaced

anthropometric measurements as a more reliable method for identifying persons having a prior record,

often under an alias name, in a criminal record repository.

Errors in identification or processing

Below are cases of errors in fingerprint identification; however, some cases involved misfiling of fingerprints or suspect profiling which slanted interpretation, rather than faults by objective matches from fingerprint search technology.

Stephan Cowans

Error in identification. Stephan Cowans (d. 2007-10-25) was convicted of attempted murder in 1997 after he was accused of the shooting of a police officer while fleeing a robbery in Roxbury, Massachusetts. He was implicated in the crime by the testimony of two witnesses, one of whom was the victim. The other evidence was a fingerprint on a glass mug that the assailant drank water from, and experts testified that the fingerprint belonged to him. He was found guilty and sent to prison with a sentence of 35 years. While in prison he earned money cleaning up biohazards until he could afford to have the evidence tested for DNA. The DNA did not match his, but he had already served six years in prison before he was released.

What is Forensic Science?

Forensic science is a scientific method of gathering and examining evidence. Crimes are solved with the use of pathological examinations that gather fingerprints, palm prints, footprints, tooth bite prints, blood, hair and fiber samples. Handwriting and typewriting samples are studied, including all ink, paper, and typography. Ballistics techniques are used to identify weapons as well as voice identification techniques are used to identify criminals.

History of Forensic Science

The first recorded application of medical knowledge to the solution of crime. In the 1248 Chinese book

Hsi DuanYu or the Washing Away of Wrongs, ways to distinguish between death by drowning or death

by strangulation were described.

Italian doctor, Fortunatus Fidelis is recognized as being the first person to practice modern forensic

medicine, beginning in 1598. Forensic medicine is the "application of medical knowledge to legal

questions." It became a recognized branch of medicine in the early 19th century.

Subdivisions of forensic science

• Criminalistics is the application of various sciences to answer questions relating to examination and comparison of biological evidence, trace evidence, impression evidence (such as fingerprints,


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footwear impressions, and tire tracks), controlled substances, ballistics (firearm examination), and other evidence in criminal investigations. Typically, evidence is processed in a crime lab.

• Digital forensics is the application of proven scientific methods and techniques in order to recover data from electronic / digital media. DF specialist work in the field as well as in the lab.

• Forensic anthropology is the application of physical anthropology in a legal setting, usually for the recovery and identification of skeletonized human remains.

• Forensic archaeology is the application of a combination of archaeological techniques and forensic science, typically in law enforcement.

• Forensic DNA analysis takes advantage of the uniqueness of an individual's DNA to answer forensic questions such as determining paternity/maternity or placing a suspect at a crime scene.

• Forensic entomology deals with the examination of insects in, on, and around human remains to assist in determination of time or location of death. It is also possible to determine if the body was moved after death.

• Forensic geology deals with trace evidence in the form of soils, minerals and petroleums. • Forensic Interviewing is a method of communicating designed to elicit information and evidence. • Forensic meteorology is a site specific analysis of past weather conditions for a point of loss. • Forensic odontology is the study of the uniqueness of dentition better known as the study of teeth. • Forensic pathology is a field in which the principles of medicine and pathology are applied to

determine a cause of death or injury in the context of a legal inquiry. • Forensic psychology is the study of the mind of an individual, using forensic methods. Usually it

determines the circumstances behind a criminal's behavior. • Forensic toxicology is the study of the effect of drugs and poisons on/in the human body. • Forensic Document Examination or Questioned Document Examination is the discipline that

answers questions about a disputed document using a variety of scientific processes and methods. Many examinations involve a comparison of the questioned document, or components of the document, to a set of known standards. The most common type of examination involves handwriting wherein the examiner tries to address concerns about potential authorship.

Forensic Science and Police Sciences

Forensic Science and Police Sciences are two areas of study that both take a scientific approach to

learning in relation to law and law enforcement. Forensic Science being the practice and application of

science to the law whereby Police Sciences enable the practice of law enforcement using the latest

technological, scientific and social science knowledge

Forensic Science

It is a very broad subject that encompasses knowledge and practice from a wide range of scientific

disciplines to provide evidence in judicial investigation.


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Forensic scientists are often involved in the search for and examination of various forms of trace evidence

such as blood, body fluids, fibres, hairs, paint, glass, footwear, tool and tyre marks, flammable

substances, explosives, drugs and poisons etc.

Police Sciences

Police Sciences enable the practice of law enforcement using the latest technological, scientific and social

science knowledge.

It is the application of scientific techniques that support the practical approach to the prevention and

detection of crime and anti-social behaviour, whilst engaging with communities. It involves knowledge of

policing styles, law, duties and powers, interview techniques, case file preparation, scenes of crime work

as well as leadership and team work approaches.

Collecting Evidence

• The physical evidence that should be collected include hairs, fibers, blood,

glass, soil, fabric impressions (in a car or on furniture)

• Particular attention is paid to cross-transfer of evidence between the

perpetrator and the weapon and/or victim

• Clothing from the suspect may be collected and must be bagged separately

• Areas of the crime scene may be vacuumed and the sweeping submitted to

the lab for testing

• Physical evidence must be collected in such a way that prevents any

change between the crime scene and the crime lab

Forensic Science Specialties

Four major areas of examination:

– Biological evidence

– Forensic Chemistry

– Pattern evidence

– Other patterns (scene reconstruction)

Forensic Pathology:

• Pathology is a specialty area of medicine


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• Pathology is the study of diseases and the bodily changes caused by the diseases

• Forensic pathologists determine the cause of death (the medical reason why a person

died; e.g. asphyxiation)

• Forensic pathologists determine the manner of death (the circum-

stances causing death; e.g. homicide)

Forensic anthropologists:

– Can determine whether found remains are of human or animal origin

– Reconstruct the skeleton from found remains

– Provide an estimate of age, stature, and gender

– Can sometimes determine racial origin

– Detect skeletal abnormalities and any trauma

– Can provide information about the cause of death


– Can determine whether found remains are

of human or animal origin







– Can determine whether found remains are of human or animal origin






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Forensic Engineering:

• Involved in the investigation of transportation related accidents, material failures, and

structural failures

Forensic Computer Science:

• Use information located on computers and other electronic devices as investigative aids

• Find hidden or deleted information to determine if internet based crimes have been

committed

Criminalistics:

• Criminalistics involves the examination, identification, and interpretation of items of

physical evidence

How does forensic identification work?

Any type of organism can be identified by examination of DNA sequences unique to that species.

Identifying individuals within a species is less precise at this time, although when DNA sequencing

technologies progress farther, direct comparison of very large DNA segments, and possibly even whole

genomes, will become feasible and practical and will allow precise individual identification.

To identify individuals, forensic scientists scan 13 DNA regions that vary from person to person and use

the data to create a DNA profile of that individual (sometimes called a DNA fingerprint). There is an

extremely small chance that another person has the same DNA profile for a particular set of regions.

Some Examples of DNA Uses for Forensic Identification

• Identify potential suspects whose DNA may match evidence left at crime scenes.

• Exonerate persons wrongly accused of crimes.

• Identify crime and catastrophe victims.

• Establish paternity and other family relationships.

• Identify endangered and protected species as an aid to wildlife officials (could be used for

prosecuting poachers).

• Detect bacteria and other organisms that may pollute air, water, soil, and food.

• Match organ donors with recipients in transplant programs.


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• Determine pedigree for seed or livestock breeds.

• Authenticate consumables such as caviar and wine.

How is DNA typing done?

Only one-tenth of a single percent of DNA (about 3 million bases) differs from one person to the next.

Scientists can use these variable regions to generate a DNA profile of an individual, using samples from

blood, bone, hair, and other body tissues and products.

In criminal cases, this generally involves obtaining samples from crime-scene evidence and a suspect,

extracting the DNA, and analyzing it for the presence of a set of specific DNA regions (markers).

Scientists find the markers in a DNA sample by designing small pieces of DNA (probes) that will each

seek out and bind to a complementary DNA sequence in the sample. A series of probes bound to a DNA

sample creates a distinctive pattern for an individual. Forensic scientists compare these DNA profiles to

determine whether the suspect's sample matches the evidence sample. A marker by itself usually is not

unique to an individual; if, however, two DNA samples are alike at four or five regions, odds are great

that the samples are from the same person.

If the sample profiles don't match, the person did not contribute the DNA at the crime scene.

If the patterns match, the suspect may have contributed the evidence sample. While there is a chance that

someone else has the same DNA profile for a particular probe set, the odds are exceedingly slim. The

question is, How small do the odds have to be when conviction of the guilty or acquittal of the innocent

lies in the balance? Many judges consider this a matter for a jury to take into consideration along with

other evidence in the case. Experts point out that using DNA forensic technology is far superior to

eyewitness accounts, where the odds for correct identification are about 50:50.

The more probes used in DNA analysis, the greater the odds for a unique pattern and against a

coincidental match, but each additional probe adds greatly to the time and expense of testing. Four to six

probes are recommended. Testing with several more probes will become routine, observed John Hicks

(Alabama State Department of Forensic Services). He predicted that DNA chip technology (in which

thousands of short DNA sequences are embedded in a tiny chip) will enable much more rapid,

inexpensive analyses using many more probes and raising the odds against coincidental matches.

Is DNA effective in identifying persons?

DNA identification can be quite effective if used intelligently. Portions of the DNA sequence that vary the most among humans must be used; also, portions must be large enough to overcome the fact that human mating is not absolutely random.

Consider the scenario of a crime scene investigation . . .


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Assume that type O blood is found at the crime scene. Type O occurs in about 45% of Americans. If investigators type only for ABO, finding that the "suspect" in a crime is type O really doesn't reveal very much.

If, in addition to being type O, the suspect is a blond, and blond hair is found at the crime scene, you now have two bits of evidence to suggest who really did it. However, there are a lot of Type O blonds out there.

If you find that the crime scene has footprints from a pair of Nike Air Jordans (with a distinctive tread design) and the suspect, in addition to being type O and blond, is also wearing Air Jordans with the same tread design, you are much closer to linking the suspect with the crime scene.

In this way, by accumulating bits of linking evidence in a chain, where each bit by itself isn't very strong but the set of all of them together is very strong, you can argue that your suspect really is the right person.

With DNA, the same kind of thinking is used; you can look for matches (based on sequence or on numbers of small repeating units of DNA sequence) at many different locations on the person's genome; one or two (even three) aren't enough to be confident that the suspect is the right one, but four (sometimes five) are used. A match at all five is rare enough that you (or a prosecutor or a jury) can be very confident ("beyond a reasonable doubt") that the right person is accused.

What are some of the DNA technologies used in forensic investigations?

PCR Analysis

Polymerase chain reaction (PCR) is used to make millions of exact copies of DNA from a biological

sample. DNA amplification with PCR allows DNA analysis on biological samples as small as a few skin

cells. With RFLP, DNA samples would have to be about the size of a quarter. The ability of PCR to

amplify such tiny quantities of DNA enables even highly degraded samples to be analyzed. Great care,

however, must be taken to prevent contamination with other biological materials during the identifying,

collecting, and preserving of a sample.

STR Analysis

Short tandem repeat (STR) technology is used to evaluate specific regions (loci) within nuclear DNA.

Variability in STR regions can be used to distinguish one DNA profile from another. The Federal Bureau

of Investigation (FBI) uses a standard set of 13 specific STR regions for CODIS. CODIS is a software

program that operates local, state, and national databases of DNA profiles from convicted offenders,

unsolved crime scene evidence, and missing persons. The odds that two individuals will have the same

13-loci DNA profile is about one in a billion.

Some Interesting Uses of DNA Forensic Identification


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The DNA Shoah Project

The DNA Shoah Project is a genetic database of people who lost family during the Holocaust. The

database will serve to reunite families separated during wartime and aid in identifying victims who

remain buried anonymously throughout Europe.

Wine Heritage

Using DNA fingerprinting techniques akin to those used to solve crimes and settle paternity suits,

scientists at the University of California, Davis, have discovered that 18 of the world's most renowned

grapevine varieties, or cultivars are close relatives. These include varieties long grown in northeastern

France such as Chardonnay, the "king of whites," and reds such as Pinot and Gamay noir, are close

relatives.

Migration Patterns

Evolutionarily stable mitochondrial DNA and Y chromosomes have allowed bioanthropologists to begin

to trace human migration patterns around the world and identify family lineage

What behavior to criminalize

Behavior can be regulated by the civil law (including administrative law) or the criminal law. In deciding to criminalize particular behavior, the legislature is making the political judgment that this behavior is sufficiently culpable to deserve the stigma of being labelled as a crime. In law, corporations can commit the same offences as natural persons. Simpson (2002) avers that this process should be straightforward because a state should simply engage in victimology to identify which behavior causes the most loss and damage to its citizens, and then represent the majority view that justice requires the intervention of the criminal law. But states depend on the business sector to deliver a stable economy, so the politics of regulating the individuals and corporations that supply that stability become more complex. For the views of Marxist criminology, see Snider (1993) and Snider & Pearce (1995), for Left realism, see Pearce & Tombs (1992) and Schulte-Bockholt (2001), and for Right Realism, see Reed & Yeager (1996). More specifically, the historical tradition of sovereign state control of prisons is ending through the process of privatisation. Corporate profitability in these areas therefore depends on building more prison facilities, managing their operations, and selling inmate labor. In turn, this requires a steady stream of prisoners able to work. (Kicenski: 2002)

The majority of crimes are committed because the offender has the 'right opportunity', i.e., where the offender simply sees the chance and thinks that he or she will be able to commit the crime and not be detected. For the most part, greed, rather than conceit, is the motive, and the rationalisation for choosing to break the law usually arises out of a form of contempt for the victim, namely that he, she or it will be powerless to prevent it, and has it coming for some reason. For these purposes, the corporation is the vehicle for the crime. This may be a short-term crime, i.e., the corporation is set up as a shell to open credit trading accounts with manufacturers and wholesalers, trades for a short period of time and then disappears with the revenue and without paying for the inventory. Alternatively and most commonly, the primary purpose of the corporation is as a legitimate business, but criminal activity is secretly intermixed with legal activity to escape detection. To achieve a suitable level of secrecy, senior managers will usually


http://public.arl.arizona.edu/shoah/

http://www.sciencemag.org/cgi/content/full/285/5433/1470

http://en.wikipedia.org/wiki/Civil_law_%28common_law%29

http://en.wikipedia.org/wiki/Administrative_law

http://en.wikipedia.org/wiki/Criminal_law

http://en.wikipedia.org/wiki/Legislature

http://en.wikipedia.org/wiki/Culpable

http://en.wikipedia.org/wiki/Victimology

http://en.wikipedia.org/wiki/Citizen

http://en.wikipedia.org/wiki/Justice

http://en.wikipedia.org/wiki/Marxist_criminology

http://en.wikipedia.org/wiki/Marxist_criminology

http://en.wikipedia.org/wiki/Left_realism

http://en.wikipedia.org/wiki/Right_Realism

http://en.wikipedia.org/wiki/Sovereignty

http://en.wikipedia.org/wiki/Prison

http://en.wikipedia.org/wiki/Privatisation

http://en.wikipedia.org/wiki/Prison

http://en.wikipedia.org/wiki/Greed

http://en.wikipedia.org/wiki/Conceit

http://en.wikipedia.org/wiki/Inventory

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be involved. The explanations and exculpations may therefore centre around rogue individuals who acted outside the organizational structures, or there may be a serious examination of the occupational and organisational structures (often hinged on the socio-economic system, gender, racism and/or age) that facilitated the criminal conduct of a corporation

Bribery and corruption are problems in the developed world, and the corruption of public officials is thought to be a primary cause of crime in developing societies, where massive foreign debt often undermines the provision government services. Peèar (1996), in discussing the implications for policing in Eastern Europe as it seeks to adapt its laws to match a capitalist model, points to the difficulty of distinguishing between lack of morality and criminality in economic crimes that tend to emerge from the structural relationships in modern commerce.

What penalties to impose

In part, this will be a function of the public perception of the degrees of socialogy culpability involved. Weissman and Mokhiber (1999) catalog the silence and indifference of the major media in the face of the widespread corporate corruption. Only in part is this justifiable. The news media find it difficult to respond to corporate crime both because reporting may compromise the trial by tainting the jury's perceptions, or because of the danger of defamation proceedings. Further, major corporate crime is often complicated and more difficult to explain to the lay public, as against street or property crimes, which may provide graphic visual evidence of harm to victims injured, or of property that has been damaged or vandalized in spectacular fashion. But, more significantly, the news media are owned by large corporations which may also own prisons. Thus, the political decisions on the resources to allocate to investigate and prosecute will tend to match the electorate's understanding of the dangers posed by 'crime'. In sentencing, the fact that the convicted individuals may have had an impeccable character as presidents, CEOs, chairmen, directors and managers is likely to be a mitigating factor.

Examples of criminal behavior in most jurisdictions include: insider trading, antitrust violations, fraud (usually involving the consumers), damage to the environment, exploitation of labour in violation of labor and health and safety laws, and the failure to maintain a fiduciary responsibility towards stockholders.

Criminals caught on tape

"Video analysis is the new DNA for law enforcement," says Grant Fredericks, a national video forensics expert and lead instructor to the Law Enforcement and Emergency Services Video Association (LEVA). "It is the next generation of investigation. Every police department in the country will have to have the ability to process video, just like they have police cars and officers have guns."

To aid in the processing and analysis of video evidence, and provide a conduit to link police agencies with related video evidence, the Department of Justice and the International Association of Chiefs of Police (IACP) have developed four Regional Forensic Video Analysis Labs. Located in Cincinnati, Ohio; Fort Worth, Texas; Raynham, Massachusetts; and a fourth location


http://en.wikipedia.org/wiki/Bribery

http://en.wikipedia.org/wiki/Political_corruption

http://en.wikipedia.org/wiki/Morality

http://en.wikipedia.org/wiki/Culpability

http://en.wikipedia.org/wiki/Trial_%28law%29

http://en.wikipedia.org/wiki/Jury

http://en.wikipedia.org/wiki/Defamation

http://en.wikipedia.org/wiki/Property_crime

http://en.wikipedia.org/wiki/Vandalize

http://en.wikipedia.org/wiki/CEO

http://en.wikipedia.org/wiki/Chairman_of_the_board

http://en.wikipedia.org/wiki/Board_of_directors

http://en.wikipedia.org/wiki/Insider_trading

http://en.wikipedia.org/wiki/Antitrust

http://en.wikipedia.org/wiki/Fraud

http://en.wikipedia.org/wiki/Natural_environment

http://en.wikipedia.org/wiki/Exploitation

http://en.wikipedia.org/wiki/Health_and_safety

http://en.wikipedia.org/wiki/Fiduciary

http://en.wikipedia.org/wiki/Stockholder

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yet to be determined in the northwestern United States, these regional labs will be the topic of Frederick's presentation, "Pursuing a Regional Approach to Video Analysis," at the upcoming Enforcement Expo in Cleveland, Ohio, July 11-12.

Abundant evidence

Since 9/11 the proliferation of video evidence has been tremendous. The average person in an urban setting is captured on video 20 to 100 times each day. And, Fredericks sees the United States moving in the same direction as the United Kingdom where there is one video camera for every two to three citizens. "There is a projected growth in the visual security industry of 13 percent per year, and I certainly don't see that waning at all," he says.

Surpassing DNA, fingerprints and eyewitness testimony, "there is more video available to law enforcement in a crime that occurs in a public area than any other kind of evidence," says Fredericks. Even with this abundance of information, only approximately 1,000 of the more than 17,000 police agencies in the United States have forensic video analysis capabilities. "The regional labs would help put investigators in touch with neighboring agencies that have the skills, knowledge and interoperable tools to both process and share appropriate information," describes Fredericks.

Although designed to be information clearinghouses, the labs will be equipped with dTective, a suite of forensic video analysis tools from Ocean Systems, currently in use by 90 percent of all agencies with video analysis capabilities. Therefore, if the expertise does not exist locally, the regional labs may become involved in the processing of evidence.

Just as DNA has CODIS and fingerprints have AFIS, now forensic video evidence will have the Regional Forensic Video Analysis Labs — a national database of criminals caught on tape. "There was no mechanism in place to share the processing knowledge, skills and equipment, and certainly no mechanism to share the resultant information," says Fredericks. "But now these are just the first of what we believe will be many crime labs around the country that will link agencies together using the same technology for the same purpose."

Sound interpretation

Equally important to the sharing of video evidence is the accurate interpretation of it. There are adages that proclaim, "Video speaks for itself" and "A picture is worth a thousand words." "That is not true," says Fredericks. "Video cannot speak for itself because the vast majority of video is either misinterpreted or the full value of the video is lost when it comes down to the analysis."

This is especially a problem with digital, time-lapse video. "I've seen a lot of video evidence in which the compression and encoding process actually caused significant errors, placing people in positions they weren't," says Fredericks, who has his own private forensic video consulting firm, Forensic Video Solutions.


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Upon Frederick's examination of the video, he discovered an encoding error. "The system didn't know where to place the suspect as he was walking forward, so it recovered an image that had occurred a few moments earlier and just represented it, making it look like he had stepped backwards," he describes.

Fredericks demonstrated that all the motion, lighting and reflection artifacts, as well as every pixel, were the same between the two frames — something that only occurs when the second frame is a reproduction of the first. "This was instrumental in proving the video was inaccurate and was not what occurred, which is why the police officer made his decision to fire," explains Fredericks. "Had the video not been properly interpreted, that officer would probably be in jail today."

Rewarding work

It is this Michigan case, and others like it, which makes Fredericks' work so rewarding. While traveling as the digital media consultant for the IACP's In-car Camera Project, Fredericks has been asked to consult on many homicides of police officers. "You'd be surprised how many police officers are murdered in the course of their duty and the amount of evidence which is captured on video," he says.

In cases in which there appeared to be no evidence initially, Fredericks has been able to identify suspects, vehicles of interest and other information which led to the identification, location and conviction of cop killers. "I've been able to help the video speak for the officer when the officer is not able to speak for himself," he says.

A former police officer, canine handler and coordinator of the Vancouver (British Columbia) Police Forensic Video Unit, Fredericks has lived law enforcement from many different angles, and this "is easily the most rewarding law enforcement job I've ever had."

Challenges in the industry

According to Grant Fredericks, a national video forensics expert, the biggest challenge facing the video evidence industry is dealing with the more than 3,000 different digital recording technologies in use. "Each one of them has its own way of processing, outputting and encoding evidence," he says. "Analysts have to be prepared to deal with an unlimited and overwhelming variance in technology."

But Fredericks does not see a national standard as a solution to this problem, as this would limit the research, development and advancement of the technology. Instead, he sees the answer in the presidential directives on interoperability, which dictate a technology must be interoperable to receive federal grant funding. "A manufacturer can produce a proprietary technology, but then it needs to output to a standard file format that can be read by any Windows-based media computer," he gives as an example.


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Currently, many police agencies are choosing low-quality proxy outputs as the interoperable component. Because of this, much of the forensic value is being stripped from the video. Fredericks says the question to be satisfied is, "Does the output video accurately represent the truth of what occurred in front of the camera?" Despite the compression and alteration that may take place because of the interoperable component, the proprietary element, the original data recorded, must be available for later analysis and examination at trial.

LifeGuard tracks criminals where they hide

"A Flock of Seagulls" once crooned, "You're trying to hide away from me, away from me. Don't you know that you can run but you can't hide away?"

Criminals will soon find truth in those lyrics if they try to conceal themselves from the long arm of the law. DKL International now offers a solution to help law enforcers find bad guys wherever they hide.

The Vienna, Virginia, company, offers LifeGuard, a handheld ultra-low frequency electric field detector designed to spot a human electric field. With this device in hand, officers can scan buildings, vehicles or other areas where direct observation of the presence of human beings is prevented or dangerous.

To date, LifeGuard is prominently used in Asia, where public safety officials deploy it to track signs of life after earthquakes and mining disasters, detect people in burning structures, scan shipping containers, and hunt for illegal immigrants on coastal freighters or fishing boats. DKL also positioned LifeGuard teams at the World Trade Center for the first 10 days after 9/11, and these searchers were able to find numerous missing rescue workers.

"Law enforcement folks really need to see this unit," says Chief Stan Tarnowski, suppression section chief at Georgia Fire Academy, a division of the Georgia Public Safety Training Center. "With all the hurricanes, natural disasters and other things we face every day, this equipment should be placed on every rescue truck and patrol vehicle in every fire and police department."

LifeGuard basics

The DKL LifeGuard, Model 1, is a handheld instrument, weighing about 2 pounds. The black plastic case has a pistol grip handle and can be configured for both long- and short-range operations. The range adjustment device (RAD) on the LifeGuard's snout, resembles an antenna, but instead of receiving an electromagnetic signal as a radio or TV antenna does, it detects the edge of an electric field.

Model 25, currently in the prototype phase, is smaller in size than Model 1. This second-generation product will be able to detect people through 1-meter-thick concrete walls within a range of 20 to 50 meters. Designed for the rugged public safety environment, this prototype will also feature reduced battery weight and size, as well as present digital readouts of detection data.


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Detecting life

The unit locates and points toward an irregular electric field generated by the human body. Electricity produced by the heart, which makes up 97 percent of this electric field, creates electrical impulses at ultra-low frequencies (less than 30 cycles per second), which travel through barriers that absorb or reflect higher frequency energy.

While the system could be used to detect a variety of electrical frequencies, its designers matched the instrument to a human being's electric field, Sidman says. Because the heart produces the majority of a person's electrical field, the system can find individuals — even when they are immobilized — as long as their heart is beating.

Pinpoint accuracy

That's a burning question on everyone's minds, admits Sidman, especially since a 1998 test of the product by Sandia National Laboratories reported the system had just six successes in 25 trials.

Sidman explains the negative reports pertain to a prototype that never went into production and no longer exists. He states, "Since we've brought the Model 1 out, 3 1/2 years after the report, we've continued to improve the product, having made five or six hardware changes and improved the software an equal number of times."

He attributes the negative reports to a discrepancy in the definition of a successful detection. Sandia researchers labeled a successful detection as when the device pinpointed a person's location with 100-percent accuracy. "If we were off by a couple of degrees at maximum range, we didn't get any credit," Sidman explains. But that's not how the device works. The LifeGuard points users in a subject's general direction then becomes more accurate as the operator closes in on the target.

Success also varies by the number of barriers between the device and a subject. "If you are in the open air, it points right at the subject," Sidman explains. But if an officer is 300 to 400 meters away from a person, and there is a lot of barrier (trees, concrete walls, etc.) between them, the device will only point the user in a direction in which to move. The system may be 5 to 6 degrees variant from where the person actually is but as the officer moves closer, and the amount of barrier is reduced, accuracy improves.

"For a search in the woods, we can get within visual distance of where that person is," Sidman says. Once officers close in, they should employ faster procedures, such as search dogs, night vision, or foot pursuits, he adds.

The device can quickly search large spaces to reduce the target search area, which may have a 180-degree arch at the pursuit's onset. "The value is that we can explore that 180-degree arch out to 400 to 500 meters, and if there's someone within that detection range, we can provide a narrower bearing," says Sidman. "Then rather than search the entire 180-degree arch, officers can head out in a 4- to 5-degree area." Its strength is its consistency, he adds. "It's not one of


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those things that works one time, and then five times it doesn't." This spells bad news for crooks hoping to outrun the long arm of the law. When officers are armed with a LifeGuard, suspects can run but they can no longer hide.

Conclusion

A crime is committed. The deed is done. Out of sight. Out of hearing. But there is always the silent witness to testify. It is impossible for the criminal to act without leaving traces, some which are so minute they need the most advanced scientific technology to detect. The first person to formally state this principle was Dr. Edmond Locard. Like a tribesman who can track the spoor of animals, forensic scientists use all their intuition, and scientific skills to patiently observe the evidence of a crime. This evidence is the silent witness.

References

1. Tewari RK, Ravikumar KV. History and development of forensic science in India. J. Postgrad Med 2000,46:303-308.

2. Zabell, Sandy "Fingerprint Evidence" Journal of Law and Policy. 3. Specter, Michael "Do Fingerprints Lie" The New Yorker. 4. Olsen, Robert D., Sr. (1972) “The Chemical Composition of Palmar Sweat” Fingerprint

and Identification Magazine Vol 53(10). 5. Turvey, B., "CP101: An Introduction to Criminal Profiling", Online Course,

http://www.corpus-delicti.com, May 1997.


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