Development of a new methodology for iris algorithm in biometric authentication using hamming distance concepts
N. Jagadeesh, Chandrashekar M Patil · 2017
Biometrics are automated methods of identifying a person or verifying the identity of a person based on a physiological or behavioral characteristic. Biometric-based authentication is the automatic identity verification, based on individual physiological or behavioral characteristics, such as fingerprints, voice, face and iris. Since biometrics is extremely difficult to forge and cannot be forgotten or stolen, Biometric authentication offers a convenient, accurate, irreplaceable and high secure alternative for an individual, which makes it has advantages over traditional cryptography-based authentication schemes. In the recent years, this biometrics has become most identifiable method of recognizing the person in all round fields & is gaining prominence in the defense, banking, retail, consumer product, examinations, etc. In this context, a sincere effort is being made to develop some novel method of identifying a person in form of developing a unique biometric identification system that has got some good advantages over the existing methodologies in the current scenario. Fast processing algorithms are being developed by keeping into mind the speed of computation (3–4 secs). The huge database is being considered to start with, followed by the pre-processing, segmentation, normalization, feature extraction & the matching scenario with the final matched results. The features of the input eye image are compared with that of the features that is already stored in the database and if it matches, the corresponding eye image is identified otherwise it remains unidentified. In our research work, since a bitwise comparison is necessary, we have chosen the hamming distance is chosen for identification. One advantage of the methodology developed in the research work considered is the speed of computation & the simplicity of the biometric recognition system developed so that it is user friendly and any layman can operate it. In this paper, we present the methodology, i.e., the algorithm that we have adopted to develop the iris recognition algorithm in a huge set of captured databases.