An assembled matrix distance metric for 2DPCA-based image recognition

Authors:
Wangmeng Zuo;David Zhang;Kuanquan Wang
Affiliations:
Department of Computer Science and Technology, Harbin Institute of Technology, 150001 Harbin, China and Biometrics Research Centre, Department of Computing, The Hong Kong Polytechnic University, H ...;Biometrics Research Centre, Department of Computing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong;Department of Computer Science and Technology, Harbin Institute of Technology, 150001 Harbin, China
Venue:
Pattern Recognition Letters
Year:
2006

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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.