This article is part of the series Advanced Image Processing for Defense and Security Applications.

Open Access Research Article

The Complete Gabor-Fisher Classifier for Robust Face Recognition

Vitomir Štruc* and Nikola Pavešić

Author Affiliations

Laboratory of Artificial Perception, Systems and Cybernetics, Faculty of Electrical Engineering, University of Ljubljana, SI-1000 Ljubljana, Slovenia

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EURASIP Journal on Advances in Signal Processing 2010, 2010:847680  doi:10.1155/2010/847680


The electronic version of this article is the complete one and can be found online at: http://asp.eurasipjournals.com/content/2010/1/847680


Received: 2 December 2009
Revisions received: 15 April 2010
Accepted: 20 April 2010
Published: 24 May 2010

© 2010 The Author(s).

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper develops a novel face recognition technique called Complete Gabor Fisher Classifier (CGFC). Different from existing techniques that use Gabor filters for deriving the Gabor face representation, the proposed approach does not rely solely on Gabor magnitude information but effectively uses features computed based on Gabor phase information as well. It represents one of the few successful attempts found in the literature of combining Gabor magnitude and phase information for robust face recognition. The novelty of the proposed CGFC technique comes from (1) the introduction of a Gabor phase-based face representation and (2) the combination of the recognition technique using the proposed representation with classical Gabor magnitude-based methods into a unified framework. The proposed face recognition framework is assessed in a series of face verification and identification experiments performed on the XM2VTS, Extended YaleB, FERET, and AR databases. The results of the assessment suggest that the proposed technique clearly outperforms state-of-the-art face recognition techniques from the literature and that its performance is almost unaffected by the presence of partial occlusions of the facial area, changes in facial expression, or severe illumination changes.

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