BIOMETRICS IN PATTERN RECOGNITION
ABSTRACT: Biometrics, recognition based on distinct personal traits has the potential to become an irreplaceable part of many identification systems. With the availability of inexpensive biometric sensors, it is increasingly clear that broader usage of biometric technology is being studied by the lack of understanding of four fundamental problems.
Those are:
Ø How to accurately and efficiently represent and recognize biometric patterns?
Ø How to guarantee that the sensed measurements are not false?
Ø How to make sure that the application is indeed exclusive using pattern recognition for an expressed purpose?
Ø How to acquire repeatable and distributive patterns from a broad population?
Biometrics refers to recognition of people based on their distinctive anatomies viz., through face, fingerprints, iris, retina, and hand geometry.In this paper the process of positive identification, the methods like screening, large scale identification, security, privacy techniques have been employed to get a reliable output for the give biometric input samples.
PAPER :
Biometrics
Biometrics is the science of verifying the identity of an individual through physiological measurements or behavioral traits. Since biometric identifiers are associated permanently with the user they are more reliable than token or knowledge based authentication Methods.
Biometrics offers several advantages over traditional security measures. These include:
1. Non-repudiation:
As Biometrics is indefinitely associated with a user, and hence it cannot be lent or stolen making repudiation infeasible. With token and password based approaches, the perpetrator can always deny committing the crime pleading that his/her password or ID was stolen or compromised even when confronted with an electronic audit trail. There is no way in which his claim can be verified effectively. This is known as the problem of deniability or of ’repudiation’.
2. Accuracy and Security:
Biometric authentication systems require the physical presence of the user. So, it is less vulnerable to dictionary and brute force style attacks. Biometrics has also been shown to possess a higher bit strength compared to password based systems and are therefore inherently secure.
3. Screening Applications:
In screening applications, we are interested in preventing the users from assuming
multiple identities (e.g. a terrorist using multiple passports to enter a foreign country).Such screening is not possible using traditional authentication mechanisms and biometrics provides the only available solution.
ARCHITECTURE
The architecture of a general biometric system consists of several stages.
a) Input device - to acquire and digitize the biometric signal such as face or fingerprint.
b) Feature extraction module - extracts distinguishable features (e.g. minutiae for a fingerprint image.
c) Matcher module – matches the input signal features with a known match
d) Database - input signals after feature extraction stored in a database used for future reference.
The matcher arrives at a decision based on similarity of the two templates and also taking into account the signal quality and other variables. Within this framework we can identify eight locations where security attacks may occur. These are
1) Fake biometric attack : replica of original replaced with a new one
2) Denial of service attack : a tampered or destroyed sensor
3) Electronic replay attack: biometric signal obtained from an insecure link and repeatedly submitted thereby circumventing the sensor.
4) Trojan horse attack : feature extraction overridden by the attacker with a custom template
5) Snooping and tampering : feature extractor and matcher intercepted with a counterfeit signal
6) Back end attack: genuine templates replaced with the counterfeit ones.
Fingerprint as a Biometric
Fingerprints have several advantages over other biometrics, such as the following:
1) High universality
2) High permanence
3) Easy collectability
4) High distinctiveness
5) High performance
6) Wide acceptability
Fingerprint Classes: (a)Tended Arch (b)Arch (c)Right Loop (d)Left Loop (e)Whorl
General architecture of a fingerprint verification system
The fingerprint image is acquired using off-line methods such as creating an inked impression on paper or through a live capture device consisting of an optical, capacitive, ultrasound or thermal sensor. The first stage consists of standard image processing algorithms such as noise removal and smoothening. However, it is to be noted that unlike regular images, the fingerprint image represents a system of oriented texture and has very rich structural information within the image. Furthermore, the definition of noise and unwanted artifacts are also specific to fingerprints. The fingerprint image enhancement algorithms are specifically designed to exploit the periodic and directional nature of
the ridges. Finally, the minutiae features are extracted from the image and are subsequently used for matching.
Minutiae representation:
Minutiae are the most popular of all the existing representation and also form the basis of the visual matching process used by human experts. Each minutiae may be described by a number of attributes such as its position (x, y) its orientation θ, its quality
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