20 December 2013 Efficient local representations for three-dimensional palmprint recognition
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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.
© 2013 SPIE and IS&T
Bing Yang, Bing Yang, Xiaohua Wang, Xiaohua Wang, Jinliang Yao, Jinliang Yao, Xin Yang, Xin Yang, Wenhua Zhu, Wenhua Zhu, } "Efficient local representations for three-dimensional palmprint recognition," Journal of Electronic Imaging 22(4), 043040 (20 December 2013). https://doi.org/10.1117/1.JEI.22.4.043040 . Submission:
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