Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/15127
Title: An assembled matrix distance metric for 2DPCA-based image recognition
Authors: Zuo, W
Zhang, D 
Wang, K
Keywords: 2DPCA
Face recognition
Feature extraction
Image recognition
Palmprint recognition
PCA
Issue Date: 2006
Publisher: North-Holland
Source: Pattern recognition letters, 2006, v. 27, no. 3, p. 210-216 How to cite?
Journal: Pattern recognition letters 
Abstract: Two-dimensional principal component analysis (2DPCA) is a novel image representation approach recently developed for image recognition. One characteristic of 2DPCA is that it can extract feature matrix using a straightforward image projection technique. In this paper, we propose an assembled matrix distance metric (AMD) to measure the distance between two feature matrices. To test the efficiency of the proposed distance measure, we use two image databases, the ORL face database and the PolyU palmprint database. The results of our experiments show that the assembled matrix distance metric is very effective in 2DPCA-based image recognition.
URI: http://hdl.handle.net/10397/15127
ISSN: 0167-8655
EISSN: 1872-7344
DOI: 10.1016/j.patrec.2005.08.017
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