Comparison of the Legendre, Zernike and Pseudo-Zernike Moments for Feature Extraction in Iris Recognition

Author

Hosaini, Seyed Jabbar ; Alirezaee, Sh ; Ahmadi, Mahdi ; Makki, Seyed Vahab-Al Din

Author_Institution

Coll. of Yazdanpanah, Tech. & Vocational Univ., Sanandaj, Iran

fYear

2013

fDate

27-29 Sept. 2013

Firstpage

225

Lastpage

228

Abstract

In this paper we compare the performance of Legendre moments, Zernike moments and Pseudo-Zernike moments in feature extraction for iris recognition. We have increased the moment orders until the best recognition rate is achieved. Robustness of these moments in various orders has been evaluated in presence of White Gaussian Noise. Numerical results indicate that recognition rate by the Legendre, Zernike and Pseudo-Zernike moments in higher orders are approximately identical. However, average computation time for feature extraction is 4.5, 18 and. 75 seconds respectively for the Legendre, Zernike and Pseudo-Zernike moments of order 14. On the other hand, the result indicates the Legendre moment is more robust than the others against the white Gaussian noise.

Keywords

Gaussian noise; Legendre polynomials; Zernike polynomials; approximation theory; feature extraction; iris recognition; white noise; Legendre moment; Zernike moment; approximation theory; average computation time; feature extraction; iris recognition rate; moment orders; numerical analysis; pseudoZernike moment; white Gaussian noise; Feature extraction; Filtering theory; Iris recognition; Microstrip filters; Microwave filters; Optical filters; Resonator filters; Legendre moment; Pseudo-Zernike moment; Zernike moment; iris recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Communication Networks (CICN), 2013 5th International Conference on

Conference_Location

Mathura

Type

conf

DOI

10.1109/CICN.2013.54

Filename

6657988