A survey of automated biometric authentication techniques

Biometric authentication refers to the automatic identification of a person by analyzing their physiological and/or behavioral characteristics or traits. Since many physiological and behavioral characteristics are unique to an individual, biometrics provides a more reliable system of authentication than ID cards, keys, passwords, or other traditional systems. A wide variety of organizations are using automated person authentication systems to improve customer satisfaction, operating efficiency as well as to secure critical resources. Now a day an increasing number of countries including India have decided to adopt biometric systems for national security and identity theft prevention, which makes biometrics an important component in security-related applications such as: logical and physical access control, forensic investigation, IT security, identity fraud protection, and terrorist prevention or detection. Various biometric authentication techniques are available for identifying an individual by measuring fingerprint, hand, face, signature, voice or a combination of these traits. New biometric algorithms and technologies are proposed, tested, reviewed, and implemented every year. This paper aims to give a brief overview of the field of biometrics and summarize various biometric authentication techniques including its strengths and limitations.

[1]  Anil K. Jain,et al.  Integrating Faces and Fingerprints for Personal Identification , 1998, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Wilhelm Burger,et al.  Ear biometrics in computer vision , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[3]  Sharath Pankanti,et al.  Biometrics: Personal Identification in Networked Society , 2013 .

[4]  Arun Ross,et al.  An introduction to biometric recognition , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[5]  D. Sweet,et al.  A look at forensic dentistry – Part 1: The role of teeth in the determination of human identity , 2001 .

[6]  M. Grgic,et al.  A survey of biometric recognition methods , 2004, Proceedings. Elmar-2004. 46th International Symposium on Electronics in Marine.

[7]  Robert P. W. Duin,et al.  Is independence good for combining classifiers? , 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

[8]  Naser Zaeri,et al.  Minutiae-based Fingerprint Extraction and Recognition , 2011 .

[9]  Ramaswamy Palaniappan,et al.  Electroencephalogram Signals from Imagined Activities: A Novel Biometric Identifier for a Small Population , 2006, IDEAL.

[10]  S.M. Krishnan,et al.  Identifying individuals using ECG beats , 2004, 2004 International Conference on Signal Processing and Communications, 2004. SPCOM '04..

[11]  Anil K. Jain,et al.  An Introduction to Biometric Authentication Systems , 2005 .

[12]  David Zhang,et al.  Two novel characteristics in palmprint verification: datum point invariance and line feature matching , 1999, Pattern Recognit..