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Proceedings Paper

Comparative study of face recognition techniques using joint transform correlation and independent component analysis
Author(s): Abdul Alsamman
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Paper Abstract

Face recognition based on independent component analysis (ICA) has emerged as a popular approach for face recognition application. In this paper we present a comparison between various optoelectronic face recognition techniques and ICA based face recognition. Computer simulations are used to study the effectiveness of the fastICA algorithm in recognizing facial images with a high level of three-dimensional (3-D) distortion. Results are then compared to various distortion-invariant optoelectronic face recognition algorithms such as synthetic discriminant functions (SDF), projection-slice SDF, optical correlator based neural networks, and pose estimation based correlation.

Paper Details

Date Published: 28 March 2005
PDF: 8 pages
Proc. SPIE 5816, Optical Pattern Recognition XVI, (28 March 2005); doi: 10.1117/12.607976
Show Author Affiliations
Abdul Alsamman, Univ. of New Orleans (United States)

Published in SPIE Proceedings Vol. 5816:
Optical Pattern Recognition XVI
David P. Casasent; Tien-Hsin Chao, Editor(s)

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