Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/241
Title: Bidirectional PCA with assembled matrix distance metric for image recognition
Authors: Zuo, W
Zhang, DD 
Wang, K
Keywords: Face recognition
Feature extraction
Image recognition
Nearest feature line
Palmprint recognition
Principal component analysis (PCA)
Issue Date: Aug-2006
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics, Aug. 2006, v. 36, no. 4, p. 863-872 How to cite?
Journal: IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics 
Abstract: Principal component analysis (PCA) has been very successful in image recognition. Recent research on PCA-based methods has mainly concentrated on two issues, namely: 1) feature extraction and 2) classification. This paper proposes to deal with these two issues simultaneously by using bidirectional PCA (BD-PCA) supplemented with an assembled matrix distance (AMD)metric. For feature extraction, BD-PCA is proposed, which can be used for image feature extraction by reducing the dimensionality in both column and row directions. For classification, an AMD metric is presented to calculate the distance between two feature matrices and then the nearest neighbor and nearest feature line classifiers are used for image recognition. The results of the experiments show the efficiency of BD-PCA with AMD metric in image recognition.
URI: http://hdl.handle.net/10397/241
ISSN: 1083-4419
DOI: 10.1109/TSMCB.2006.872274
Rights: © 2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
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