Performance Analysis on Iris Feature Extraction Using PCA, Haar Transform and Block Sum Algorithm
Aparna Gale1, S.S.Salankar2
1Prof. Aparna Gale, Assistant Professor, Om College of Engineering Near Lloyd’s Steel Industrials, Inzapur, Wardha, India.
2Dr. S.S. Salankar, Professor, G H Raisoni College of Engineering Nagpur, India.
Manuscript received on March 03, 2015. | Revised Manuscript received on March 19, 2015. | Manuscript published on April 30, 2015. | PP: 46-49 | Volume-4 Issue-4, April 2015. | Retrieval Number: D3819044415/2013©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Iris recognition is the most accurate biometrics which has received increasing attention in departments which require high security. In this paper, we make a Comparative study of performance of image transforms using Haar transform, Principle of Component Analysis (PCA), Block sum algorithm technique for iris verification. to extract features on specific portion of the iris for improving the performance of an iris recognition system. The main aim of this paper is to show that how can we get better overall accuracy than the existing methods of feature extraction of iris recognition system. The proposed methods are evaluated by combining Haar transform and block sum algorithm based upon False Rejection Rate (FRR) and False Acceptance Rate (FAR) and the experimental results show that this technique produces good performance on CASIA VI iris database.
Keywords: Iris recognition, Biometrics, Block sum algorithm, Haar transform, PCA.