Palmprint recognition combining LBP and cellular automata

Authors:
Xiao Dong Dai;Bing Wang;Pei ZhenWang
Affiliations:
Institute of Electrical and Information, Anhui University of Technology, Maanshan, China;Institute of Electrical and Information, Anhui University of Technology, Maanshan, China;Institute of Electrical and Information, Anhui University of Technology, Maanshan, China
Venue:
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Year:
2010

Citing 10
Cited 0

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Abstract

In this paper, we present a palmprint recognition method which combines local binary pattern (LBP) and cellular automata. The LBP descriptor is proposed as a unifying texture model that describes the formation of a texture with micro-textons and their statistical placement rules. Because texture is one of the most importent features in palmprint image, so we think the features based on LBP will be good discriminative for palmprint identification. Cellular automata can be generally described as discrete dynamic systems completely defined by a set of rules in a local neighborhood. In this paper, we use cellular automata to extract features as the part of feature vector. The experiments conducted on Polytechnic University Palmprint Database I demonstrates the effectiveness of proposed method.