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Journal of Electronic Imaging

Efficient local representations for three-dimensional palmprint recognition
Author(s): Bing Yang; Xiaohua Wang; Jinliang Yao; Xin Yang; Wenhua Zhu
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Paper 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.

Paper Details

Date Published: 20 December 2013
PDF: 9 pages
J. Electron. Imag. 22(4) 043040 doi: 10.1117/1.JEI.22.4.043040
Published in: Journal of Electronic Imaging Volume 22, Issue 4
Show Author Affiliations
Bing Yang, Hangzhou Dianzi Univ. (China)
Xiaohua Wang, Hangzhou Dianzi Univ. (China)
Jinliang Yao, Hangzhou Dianzi Univ. (China)
Xin Yang, Dalian Univ. of Technology (China)
Wenhua Zhu, Hangzhou Dianzi Univ. (China)

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