Open AccessExtraction of Iris Crypt, Pigment Spot, and Wolfflin Nodule Biological Feature using Feature Point Selection Algorithms
Author(s) -
Ms. Sindu*,
B. Thiyaneswaran,
K. Anguraj,
Mr. N. S. Yoganathan
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d7910.118419
Subject(s) - iris (biosensor) , iris recognition , artificial intelligence , computer science , feature (linguistics) , feature extraction , feature selection , pattern recognition (psychology) , computer vision , biometrics , linguistics , philosophy
The iris biometrics is an important biological feature of the human. The iris is the part of human eye. The human eye consists of many features. Iris is one of the unique features of human eye. In this paper we propose an algorithm to extract the features of iris. The existing algorithms are based on combined biological features of iris. We are going to introduce separate biological features and extract them one by one using suitable algorithms. The proposed method is used to extract the biological features of human iris. The proposed method uses crypts, pigment layers, and Wolfflin nodules features of iris. Each feature is extracted initially and suitable feature selection algorithm is identified. The manual cropping is initially applied in the eye image which extracts iris layer. The manual cropping is further applied on iris to locate the biological layers. Canny edge detection is applied on each iris feature. The FAST, SURF, MinEigen, BRISK, and MSER feature points are collected from each biological layer. The MinEigen extracts 218 feature points from the crypt layer. The BRISK extracts 161 and 89 feature points from the pigment and Wolfflin nodules. The proposed system can be used in iris recognition system all over the world for various authentication and security purposes. The individual feature extraction helps to make the recognition system more secure and accurate as compared to the existing systems which uses combined biological features. Thus, the proposed system is advantageous as compared to the existing systems and the efficiency will also be high if it is used for iris recognition.