Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1201
Title: Bi-directional PCA with assembled matrix distance metric
Authors: Zuo, Wangmeng
Wang, Kuanquan
Zhang, David D.
Subjects: PCA
2DPCA
Image recognition
Face recognition
Palmprint recognition
Issue Date: 2005
Publisher: IEEE
Source: 2005 ICIP : 2005 International Conference on Image Processing (ICIP) : September 11-14, 2005, Genova, Italy, v. 2, p. 958-961.
Abstract: Principal Component Analysis (PCA) has been very successful in image recognition. Recent researches on PCA-based methods are mainly concentrated on two issues, feature extraction and classification. In this paper we propose Bi-Directional PCA (BDPCA) with assembled matrix distance (AMD) metric to simultaneously deal with these two issues. For feature extraction, we propose a BDPCA approach which can reduce the dimension of the original image matrix in both column and row directions. For classification, we present an AMD metric to calculate the distance between two feature matrices. The results of our experiments show that, BDPCA with AMD metric is very effective in image recognition.
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Type: Conference Paper
URI: http://hdl.handle.net/10397/1201
ISBN: 0780391349
Appears in Collections:COMP Conference Papers & Presentations

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