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Efficient local representations for three-dimensional palmprint recognition

[+] Author Affiliations
Bing Yang

Hangzhou Dianzi University, Institute of Cognitive and Intelligent Computing, Xiasha Higher Education Zone, 310018 Hangzhou, China

Xiaohua Wang

Hangzhou Dianzi University, Institute of Cognitive and Intelligent Computing, Xiasha Higher Education Zone, 310018 Hangzhou, China

China Jiliang University, Xueyuan Street, Xiasha Higher Education Zone, 310018 Hangzhou, China

Jinliang Yao

Hangzhou Dianzi University, Institute of Cognitive and Intelligent Computing, Xiasha Higher Education Zone, 310018 Hangzhou, China

Xin Yang

Dalian University of Technology, Computer Science and Technology College, Linggong Road, Ganjingzi District, 116024 Dalian, China

Wenhua Zhu

Hangzhou Dianzi University, Institute of Cognitive and Intelligent Computing, Xiasha Higher Education Zone, 310018 Hangzhou, China

J. Electron. Imaging. 22(4), 043040 (Dec 20, 2013). doi:10.1117/1.JEI.22.4.043040
History: Received August 21, 2013; Revised October 29, 2013; Accepted November 25, 2013
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Abstract.  Palmprints have been broadly used for personal authentication because they are highly accurate and incur low cost. Most previous works have focused on two-dimensional (2-D) palmprint recognition in the past decade. Unfortunately, 2-D palmprint recognition systems lose the shape information when capturing palmprint images. Moreover, such 2-D palmprint images can be easily forged or affected by noise. Hence, three-dimensional (3-D) palmprint recognition has been regarded as a promising way to further improve the performance of palmprint recognition systems. We have developed a simple, but efficient method for 3-D palmprint recognition by using local features. We first utilize shape index representation to describe the geometry of local regions in 3-D palmprint data. Then, we extract local binary pattern and Gabor wavelet features from the shape index image. The two types of complementary features are finally fused at a score level for further improvements. The experimental results on the Hong Kong Polytechnic 3-D palmprint database, which contains 8000 samples from 400 palms, illustrate the effectiveness of the proposed method.

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© 2013 SPIE and IS&T

Citation

Bing Yang ; Xiaohua Wang ; Jinliang Yao ; Xin Yang and Wenhua Zhu
"Efficient local representations for three-dimensional palmprint recognition", J. Electron. Imaging. 22(4), 043040 (Dec 20, 2013). ; http://dx.doi.org/10.1117/1.JEI.22.4.043040


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