Proceedings Article10.1109/ICPR.2008.4760935
An introduction to biometrics
Anil K. Jain,Arun Ross,Karthik Nandakumar +2 more
- 01 Dec 2008
- pp 1-1
717
TL;DR: In this paper, the design of a biometric system is discussed from the viewpoint of four commonly used biometric modalities -fingerprint, face, hand, and iris.
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Abstract: Summary form only given. Biometrics refers to the automatic identification (or verification) of an individual (or a claimed identity) by using certain physical or behavioral traits associated with the person. By using biometrics it is possible to establish an identity based on `who you are?, rather than by `what you possess? (e.g., an ID card) or `what you remember? (e.g., a password). Therefore, biometric systems use fingerprints, hand geometry, iris, retina, face, vasculature patterns, signature, gait, palmprint, or voiceprint to determine a person?s identity. The purpose of this tutorial is two-fold: (a) to introduce the fundamentals of biometric technology from a pattern recognition and signal processing perspective by discussing some of the prominent techniques used in the field; and (b) to convey the recent advances made in this field especially in the context of security, privacy and forensics. To this end, the design of a biometric system will be discussed from the viewpoint of four commonly used biometric modalities - fingerprint, face, hand, and iris. Various algorithms that have been developed for processing these modalities will be presented. Methods to protect the biometric templates of enrolled users will also be outlined. In particular, the possibility of performing biometric matching in the cryptographic domain will be discussed. The tutorial will also introduce concepts in biometric fusion (i.e., multibiometrics) in which multiple sources of biometric information are consolidated. Finally, there will be a discussion on some of the challenges encountered by biometric systems when operating in a real-world environment and some of the methods used to address these challenges.
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Citations
Biometrics: An Overview on New Technologies and Ethic Problems
TL;DR: This paper briefly presents some new technologies that have recently been proposed in biometrics with their levels of reliability, and discusses the different social and ethic problems that may result from the abusive use of these technologies.
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Performance Evaluation of Principal Component Analysis And Independent Component Analysis Algorithms For Facial Recognition
M A Hambali,Jimoh R. G +1 more
- 01 Jan 2015
TL;DR: Comparison study of two most popular appearance-based face recognition methods - Principal Component Analysis and Independent Component Analysis showed that Indepenedent Component Analysis (ICA) perform better in term of recognition rate and error rate, therefore it can be used for real time recognition system.
3
Multibiometric Personal Identification based on Hybrid Artificial Intelligence Technique using Serial Mode Architecture
TL;DR: A multibiometric identification system with serial mode using palmprint, Dental and DNA biometric traits is proposed to identify person and experimental results show that the proposed system has an encouraging performance.
Two-Stage Block-Based Whitened Principal Component Analysis with Application to Single Sample Face Recognition
TL;DR: This two-stage block-based whitened PCA (TS-BWPCA) is actually a coarse-to-fine scheme that can maximize both global and local scatter, and thus overcomes the aforementioned shortcomings of PCA.
Effects of Sensors, Age, and Gender on Fingerprint Image Quality
Rong Yang
- 01 Jan 2018
TL;DR: It was showed that fingerprint quality decreases with age and males have better fingerprint quality than females on most sensors and the multispectral sensor has the best and stable fingerprint image quality.
References
Eigenfaces for recognition
Matthew Turk,Alex Pentland +1 more
TL;DR: A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture.
An introduction to biometric recognition
TL;DR: A brief overview of the field of biometrics is given and some of its advantages, disadvantages, strengths, limitations, and related privacy concerns are summarized.
High confidence visual recognition of persons by a test of statistical independence
TL;DR: A method for rapid visual recognition of personal identity is described, based on the failure of a statistical test of independence, which implies a theoretical "cross-over" error rate of one in 131000 when a decision criterion is adopted that would equalize the false accept and false reject error rates.
How iris recognition works
TL;DR: Algorithms developed by the author for recognizing persons by their iris patterns have now been tested in many field and laboratory trials, producing no false matches in several million comparison tests.
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