Submit Article
Back to Journal

SM Journal of Biometrics & Biostatistics

Iris Recognition System Using PCA Based on DWT

[ ISSN : 2573-5470 ]

Abstract
Details

Received: 31-Jul-2017

Accepted: 22-Aug-2017

Published: 31-Aug-2017

Research Article | Volume 2 - Issue 3 | Article DOI :

Download PDF

Humayan Kabir Rana1, Md Shafiul Azam2 and Mst Rashida Akhtar3

1Department of CSE, Green University of Bangladesh, Bangladesh

2Department of CSE, Pabna University of Science and Technology, Bangladesh

3Department of CSE, Varendra University, Bangladesh

Corresponding Author:

Humayan Kabir Rana, Department of CSE, Green University of Bangladesh, Bangladesh

Keywords

Biometrics; Iris recognition; Hough transformation; Daugman’s rubber sheet model; Discrete wavelet transformation; Principle component analysis

Abstract

The Biometric recognition is the study of identifying individuals based on their unique physiological or behavioral characteristics, includes iris, face, fingerprint, retina, vein, hand geometry, hand writing, human gait, signature, keystrokes and voice. Among the biometrics, an iris has unique structure and it remains stable over a person life time. So that iris recognition is regarded as the most accurate and reliable biometric recognition system. In this paper, we proposed a technique that uses Principal Component Analysis (PCA) based on Discrete Wavelet Transformation (DWT) for selecting feature of iris templates to increase the efficiency of iris recognition. Basically, the idea of DWT is to convert the iris image into four frequency band. We are using one frequency band instead of four and applying PCA for further feature extraction. Experiments with iris images from the CASIA database present good results, showing that the proposed combination strategy of feature extraction is suitable for increasing accuracy of iris recognition.

Citation

Rana HK, Azam MS and Akhtar MR. Iris Recognition System Using PCA Based on DWT. SM J Biometrics Biostat. 2017; 2(3): 1015.