forensic science laboratory pin s.c.r.l. university of … was born in 2010 at the university of...
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Forensic Science Laboratory
Pin s.c.r.l.
University of Florence
FORLAB was born in 2010 at the University of Florence
from the meeting of forensic professional consultants and
academic researchers.
FORLAB studies and exploits methodologies and
techniques for the analysis and processing of audio-visual
data for forensic purposes.
FORLAB offers expertise and solutions for Magistrates,
Prosecutors, Lawyers, Law Enforcement and Citizens who
wish to receive technical assistance in their legal actions.
Also Insurances and Journalism can benefit from FORLAB.
WHO
CONSULTING: FORLAB supports in all the stages of legal
actions, following the Best Practices for handling, preserving
and processing digital evidence.
RESEARCH: FORLAB exploits the state-of-the-art
technologies and proposes the application of innovative
solutions for the analysis of multimedia content.
TRAINING: FORLAB provides scientific and technical
training to solve specific problems.
WHAT
The Forensic Analysis is carried out mainly through the
application of Multimedia Forensic Technologies.
Multimedia Forensics
Data
Question
Forensic Analysis
Analysis of results
Answer
Acquisition Methodology Technology
Digital Image life cycle
Before taking a digital content as evidence its trustworthiness
should be verified.
Any acquisition and processing step leaves on the digital data
some traces, detectable although imperceptible.
Multimedia Forensics: idea
real word
scene lenses optical filter
color
sensor
color
interpolation
in-camera software
processing (white
balancing; contrast
saturation; etc)
in-camera
Jpeg
compression
CFA
pattern
digital image
CCD/CMOS
out-camera
processing
final digital
image
Analyzing the digital footprints left by processing/acquisition, it
is possible to:
check if an image has been changed, even in small part
(photomontage)
detect the insertion, removal or alteration of frames in digital
video
study the integrity of audio recordings
What kind of footprints?
resampling, compression, non linear operations, brightness
adjustment, blurring, enhancement, cloning, splicing…
Integrity Verification
Integrity Verification
Like a gun on the bullet, the acquisition devices leave
distinctive traces on the acquired content.
Analyzing the digital footprints left by the acquisition process,
it is possible to:
distinguish if the content is real or computer generated
distinguish between different devices (camera, scanner,
etc.)
distinguish which camera captured the image
Source Identification
real or computer generated ?
which brand model specific device
which printer
Source Identification
Nikon
Canon
Pentax
Coolpix P80
Coolpix S500
What
CoolpixP60
What kind of footprints?
Color Filter Arrays and Interpolation: scanners detect all
three colors at each pixel, cameras only detect one color at
each pixel and the remaining 2 colors are estimated using
interpolation algorithms
Sensor Noise: inherent in any electronic device, measure
variations in pixel values under no light or constant light,
deterministic 2D noise template superimposed to each image
Statistical and physical properties: statistical and
geometrical features, color distribution, edge, textures…
Source Identification
Methodology
Metadata EXIF
Camera ballistic
Source detector
Results comparison & conclusions
Forgery detector
Forgery localization
Visual analysis
Other activities
Besides the specific expertise in the multimedia forensics,
FORLAB is able to perform some other kind of analysis, in
order to:
• improve the quality of the audio-visual data
• analyze the content of images and video sequences
Often the digital content is not easily ‘understandable’, due
to the poor acquisition phase (low light, insufficient
resolution…).
The application of image and video processing algorithms can
improve the intelligibility of the content, for example:
Quality improvement
increasing the contrast and lighting
integrating information from multiple
frames to increase the resolution
correcting perspective distortion
reducing blur
identification of "features" for
further processing steps
(contours, geometric shapes,
objects of predetermined
shape)
measuring objects/subjects
in the scene
extraction of information like
photogrammetric
measurements, anthropometric
characteristics of objects or
persons in the scene
Content Analysis
Perspective reconstruction
Measurement extraction
Methods to extract information from visual data can be usefully
applied:
Into the wild
Coming from the academic world, FORLAB people are
aware of the gap between scientific results and practical
reliability of forensic algorithms, thus putting a strong
effort in:
evaluating the suitability of published algorithms to real cases
developing practical solutions starting from the state-of-the-art
methods
proposing scientific methodology to support the achieved
results
studying the best way to present the results to the legal
entities
Contacts
www.forlab.org
SCIENTIFIC COORDINATOR:
Alessandro Piva, PhD
Email: [email protected]
OPERATIONS MANAGER:
Alessia De Rosa, PhD
Email: [email protected]
Work: +39 055 4796380 (extension: 2)
Mobile: +39 347 0929726
TECHNICAL MANAGERS:
Massimo Iuliani
Email: [email protected]
Work: +39 055 4796380 (extension: 4)
Mobile: +39 320 1872117
Marco Fontani
Email: [email protected]
Work: +39 055 4796380 (extension: 3)
Mobile: +39 329 5618471