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Proceedings Paper

Wavelet filtered shifted phase-encoded joint transform correlation for face recognition
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Paper Abstract

A new wavelet-filtered-based Shifted- phase-encoded Joint Transform Correlation (WPJTC) technique has been proposed for efficient face recognition. The proposed technique uses discrete wavelet decomposition for preprocessing and can effectively accommodate various 3D facial distortions, effects of noise, and illumination variations. After analyzing different forms of wavelet basis functions, an optimal method has been proposed by considering the discrimination capability and processing speed as performance trade-offs. The proposed technique yields better correlation discrimination compared to alternate pattern recognition techniques such as phase-shifted phase-encoded fringe-adjusted joint transform correlator. The performance of the proposed WPJTC has been tested using the Yale facial database and extended Yale facial database under different environments such as illumination variation, noise, and 3D changes in facial expressions. Test results show that the proposed WPJTC yields better performance compared to alternate JTC based face recognition techniques.

Paper Details

Date Published: 1 May 2017
PDF: 18 pages
Proc. SPIE 10203, Pattern Recognition and Tracking XXVIII, 1020308 (1 May 2017); doi: 10.1117/12.2262562
Show Author Affiliations
Md. Moniruzzaman, Nfina Technologies, Inc. (United States)
Mohammad S. Alam, Texas A&M Univ.-Kingsville (United States)

Published in SPIE Proceedings Vol. 10203:
Pattern Recognition and Tracking XXVIII
Mohammad S. Alam, Editor(s)

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