Topics: Biometrics, Facial recognition system, Iris recognition Pages: 16 (3305 words) Published: February 26, 2014
Volume 3, Issue 6, June 2013

ISSN: 2277 128X

International Journal of Advanced Research in
Computer Science and Software Engineering
Research Paper
Available online at:

A Review on Biometrics and Ear Recognition Techniques
Sukhdeep Singh, Dr. Sunil Kumar Singla(Assit.Prof.)
Electrical & Instrumentation Engg Dept.
Thapar University ,Patiala, India
Abstract: Biometric authentication of a person is highly challenging and complex problem. A significant research effort has gone into this areas and a number of research works were published, Biometrics is a growing technology , which has been widely used in forensics, secured access , prison security, medical, and robotics areas financial services, ecommerce, telecommunication, government, traffic, health care the security issues are more important. Recognizing people by their Ear is relatively new class of biometrics. Several reasons account for this trend: first, ear recognition does not suffer from some problems associated with other non contact biometrics ,such as face recognition; second ,shape and features of ear are unique for each person and invariant with age and structure of the ear is fairly stable and robust to change in facial expressions. It is most promising candidate for combination with the face in the context of multipose face. .In this paper we discuss different methods of Ear detection and recognition Keywords:

As our society becomes electronically connected to form one big global community through internet and other digital means, it has become necessary to carry out reliable person recognition often remotely and through automatic means. it is most important that who is who ,person who he or she claim‘s to be because of all financial transaction and of security issues too. It is important to verify that people are allowed to pass some points or use some resources [1]. The security issues are arisen quickly after some crude abuses. For these reason, organizations are interested in taking automated identity authentication systems. Biometrics is automated methods of recognizing a person based on a physiological or behavioural characteristic [18]. Usually there are different methods for verifying identity of individuals: (i) cards, badges, keys are used as identity which very common method (ii) knowledge like password, Personal Identification Number (PIN); (iii) biometrics like fingerprint recognition, face recognition , ear recognition[2]. It is divided into two parts invasive and non-invasive methods. Invasive methods are those that require the cooperation of the subject in order to acquire data needed to compare his biometric features to the ones stored in a database Such as one can allow physical access to a secure area in a building by using finger scans or can grant access to a bank account at an ATM by using retina scan.Noninvasive biometrics does not require the cooperation of the subject [18] ; in fact data capture may be done without their knowledge, Such as scanning a crowd with the help of a camera and using face recognition technology, one can verify matches that are already store in database. These biometric areas have gained the most attention among the research community [17]. There are several application areas where biometrics can be used. Basically there are two types of application scenarios. Identification, ―Who I am?‖ and verification, ―Am I who I claim I am?‖[1]. In identification there is a database with biometrics and the just taken biometric, e.g. hand shape is compared with the biometrics in database and system decides who the person is? In verification the comparison is done only with data, which is known to be valid for the approved person, e.g. the fingerprint or hand shape is included in an identification card[1]

Fig1: General Biometric System[3].
© 2013, IJARCSSE All Rights Reserved

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Singh et al., International Journal of Advanced Research in Computer Science and...

References: icmla, pp.231-238, Fifth International Conference on Machine Learning and Applications (ICMLA '06), 2006
Songklanakarin J. Sci. Technol. 34 (2) 189-194, Mar. - Apr. 2012.
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