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Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Computer Vision & Biometrics
Proma Goswami
Roll No:97/IT/130005
University Of Calcutta
21th March, 2014
Proma Goswami , Roll No:97/IT/130005 1
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Contents
Introduction to Computer vision & Biometrics
Categories of Biometrics
Vision based Biometrics
Basic characteristics of Biometric Technologies
Working principle
Fingerprint recognition
Gait analysis
Applications
Biometric system performance
Advantage & Disadvantage of these Biometric methods
Proma Goswami , Roll No:97/IT/130005 2
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Definitions
Computer vision is a field that includes methods for acquiring, processing,analyzing, and understanding images and, in general, high-dimensionaldata from the real world in order to produce numerical or symbolicinformation, e.g., in the forms of decisions
Biometric is the science and technology of measuring and analyzingbiological data. In information technology, biometrics refers totechnologies that measure and analyze human body characteristics, suchas DNA, fingerprints, eye retinas and irises, voice patterns, facialpatterns,gait and hand geometry for authentication purposes.
Proma Goswami , Roll No:97/IT/130005 3
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Why we need Biometrics
The Security field uses 3 types of authentication
Something you know:- a password, PIN, or piece of personal information(such as your mother’s maiden name)
Something you have:- a card key, smart card, or token(like a Secure IDcard)
Something you are :- a biometric.
In between these biometrics is the most secure and convenient authenticationtool. It can’t be borrowed, stolen, or forgotten, and forging one is practicallyimpossible. (Replacement part surgery, by the way, is outside the scope of thisintroduction.)
Important Statistics:-
The average adult working in a large business has 12 passwords toremember, and spends nearly a week in every year logging into systems.
The average cost to a large company for every password lost is $16
Proma Goswami , Roll No:97/IT/130005 4
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Categories & Vision based Biometrics
Vision Based Biometrics
How Computer vision isapplied in Biometrictechniques?
DNA,Hair,Speech,Odorrecognition areautomated method butnot vision basedvision-based biometrics- those that use imagesensors and algorithmsderived from machinevisionAs vision-basedBiometrics we willdiscuss Fingerprint,Gait analysis
Proma Goswami , Roll No:97/IT/130005 5
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Basic characteristics of Biometric Technologies
Universality:Every person should have the characteristic. People who aremute or without a fingerprint will need to be accommodated in some way.
Uniqueness: Generally, no two people have identical characteristics.However, identical twins are hard to distinguish.
Permanence: The characteristics should not vary with time. A person’sface, for example, may change with age.
Collectibility: The characteristics must be easily collectible andmeasurable.
Performance: The method must deliver accurate results under variedenvironmental circumstances.
Acceptability: The general public must accept the sample collectionroutines. Nonintrusive methods are more acceptable.
Circumvention: The technology should be difficult to deceive
Proma Goswami , Roll No:97/IT/130005 6
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Working principle
Biometric devices consist of a reader or scanning device software thatconverts the gathered information into digital form, and a database thatstores the biometric data with comparison with existing recordsModes:
Enrollment Mode:A sample of the biometric trait is captured, processed by a computer, and storedfor later comparison
Verification Mode:In this mode biometric system authenticates a persons claimed identity fromtheir previously enrolled pattern.
Proma Goswami , Roll No:97/IT/130005 7
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Fingerprint Recognition
Fingerprint Patterns:- Basically there are 6 classes of patterns
Proma Goswami , Roll No:97/IT/130005 8
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Fingerprint recognition
For fingerprint Recognition welook at:
Crossover:-Two ridgescross each other
Core:- Center
Bifurcation:-Ridgeseparates
Ridge ending:-End point
Pore:-Human pore
Delta:-Space betweenridges
Various Fingre print matching mechanism
Corelation based method
Minutiae based method
Ridge pattern based method
Proma Goswami , Roll No:97/IT/130005 9
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
A MINUTIAE-BASED MATCHING ALGORITHMS in FingerprintRecognition Systems
What is Minuatiae?
Ridge endings ,bifurcations on a persons finger are used to plot points know asMinutiae
Minutiae matching essentially consist of finding the best alignment between thetemplate (set of minutiae in the database) and a subset of minutiae in theinput fingerprint, through a geometric transformation.There are two processes in this algorithm
Feature Extraction
Matcher
Proma Goswami , Roll No:97/IT/130005 10
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
A MINUTIAE-BASED MATCHING ALGORITHMS in FingerprintRecognition Systems
Proma Goswami , Roll No:97/IT/130005 11
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
A MINUTIAE-BASED MATCHING ALGORITHMS in FingerprintRecognition Systems
Feature Extraction Two approaches of minutia extraction process can befound. The simplest and most used method is based on binarization andridge thinning stage. Due to a problem of the false minutiae introduced bythinning, some authors proposed direct grey-scale minutiae extraction.Ridge Thinning Method The most commonly used method of minutiaeextraction is the Crossing Number (CN) concept. There are 2 steps:-
The first step is to binarizateThin the ridges, so that they are single pixel wide.(shown in the figure)
Figure : Fingerprint image a) binarization and b) skeletonization.Proma Goswami , Roll No:97/IT/130005 12
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
A MINUTIAE-BASED MATCHING ALGORITHMS in FingerprintRecognition Systems
The minutiae points are determined by scanning the local neighbourhood ofeach pixel in the ridge thinned image, using a 33 window (Figure shown below).
Figure : a) Ridge ending and b) bifurcation in c)3× 3 window.
Proma Goswami , Roll No:97/IT/130005 13
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
A MINUTIAE-BASED MATCHING ALGORITHMS in FingerprintRecognition Systems
Now filter the image to check whether the image is in database and the imagewe get matched or not?
Figure : Procedure of Finger print recognition
Proma Goswami , Roll No:97/IT/130005 14
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
A MINUTIAE-BASED MATCHING ALGORITHMS in FingerprintRecognition Systems
Feature Extractor actually done these 3 steps
Capture Image
Enhance Ridge
Extract Minutiae
Proma Goswami , Roll No:97/IT/130005 15
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
A MINUTIAE-BASED MATCHING ALGORITHMS in FingerprintRecognition Systems
Matcher
Used to match fingerprint
Trade-off between speed and performance
Group minutiae and categorize by typeLarge number of certain type can result in faster searches
Proma Goswami , Roll No:97/IT/130005 16
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Security
Accuracy97% will return correct results100% deny intruders
Image is discardedCannot reconstruct the fingerprint from data
Proma Goswami , Roll No:97/IT/130005 17
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Gait analysis
Another new approach is biometric recognition system based on gait
Gait is a persons manner of walking
Biometric gait recognition refers to verifying and/or identifying personsusing their walking style
Human recognition based on gait is relatively recent,
Various Gait analysis mechanism
MV based method: gait is captured using a video-camera from distance
FS based: a set of sensors or force plates are installed on the flors andactivate when a person walks
WS based: In WS-based gait recognition, gait is collected using body wornmotion record- ing (MR) sensors
Here we shall discuss about MV based gait analysis
Proma Goswami , Roll No:97/IT/130005 18
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
MV based Gait recognition
BenAbdelkader et al. (2002) used stride and cadence for personidentification
Johnson and Bobick et al. (2001) extracted static body parameters suchas the height, the distance between head and pelvis, the maximumdistance between pelvis and feet
Most of the MV based gait recognition algorithms are based on the humansilhouette
What is Human Silhouette?
Figure : Example of gait detection. (a) Background image; (b) Original image; and(c) Extracted silhouette
Proma Goswami , Roll No:97/IT/130005 19
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
MV based Gait recognition
BenAbdelkader et al. (2002) used stride and cadence for personidentification
Johnson and Bobick et al. (2001) extracted static body parameters suchas the height, the distance between head and pelvis, the maximumdistance between pelvis and feet
Most of the MV based gait recognition algorithms are based on the humansilhouette
What is Human Silhouette?
Figure : Example of gait detection. (a) Background image; (b) Original image; and(c) Extracted silhouette
Proma Goswami , Roll No:97/IT/130005 19
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Silhouette based Gait Feature extraction & Recognition system
Center of Mass: At the time of walking, thecenter of mass location is noted and extracted
step size length : Boundary box mechanism isused to measure step length
Figure : Boundary box to measure width
Gait cycle length: when one foot contacts theground and ends when that foot contacts theground again
Figure : Gait CycleFigure : Gait recognition systemProma Goswami , Roll No:97/IT/130005 20
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Applications
Gait Biometric
making itwell-suited toidentifyingperpetrators at acrime scene fromCCTV footage
Military/intelligencesector
Identification ofshoplifters
Proma Goswami , Roll No:97/IT/130005 21
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Biometric system performance
Biometric systems are not perfect.There are two important types oferrors associated with biometricsystem
System decisions (i.e.accept/reject) is based onso-called thresholds
The False Acceptance is theprobability of wrongfully acceptingan impostor user
False Rejection is the probabilityof wrongfully rejecting a genuineuser.
Where FAR=FRR is known asEER at that threshold value
Figure : FAR& FRR as function ofthreshold
Proma Goswami , Roll No:97/IT/130005 22
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Advantage & Disadvantage of these Biometric methods
Finger print
AdvantageWell established forensictechnique, High accuracyModern fingerprintscanners→ Low Cost
DisadvantageFingerprints of smallfraction of population maynot be suitableLarge computation, Useracceptance ↓
Gait analysis
AdvantageIdentification in adverseconditions like smog,largedistanceAcceptable biometric likeface
DisadvantageMay not remain invariantin tiredness, age andhealthcan be obscured,wearingloose fitting clothes
Proma Goswami , Roll No:97/IT/130005 23
Introduction to Computer vision & Biometrics Usefulness of Biometric Authentication Categories of Biometrics Characteristic Working principle Fingerprint recognition Fingerprint recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Fingerprint Recognition Gait analysis Gait analysis Gait analysis Applications Performance Advantage & Disadvantage
Thank you
THANK YOUFOR YOUR ATTENTION
Proma Goswami , Roll No:97/IT/130005 24