Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/16765
Title: The multiscale competitive code via sparse representation for palmprint verification
Authors: Zuo, W
Lin, Z
Guo, Z
Zhang, D 
Issue Date: 2010
Source: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010, p. 2265-2272 How to cite?
Abstract: Palm lines are the most important features for palmprint recognition. They are best considered as typical multiscale features, where the principal lines can be represented at a larger scale while the wrinkles at a smaller scale. Motivated by the success of coding-based palmprint recognition methods, this paper investigates a compact representation of multiscale palm line orientation features, and proposes a novel method called the sparse multiscale competitive code (SMCC). The SMCC method first defines a filter bank of second derivatives of Gaussians with different orientations and scales, and then uses the l 1-norm sparse coding to obtain a robust estimation of the multiscale orientation field. Finally, a generalized competitive code is used to encode the dominant orientation. Experimental results show that the SMCC achieves higher verification accuracy than state-of-the-art palmprint recognition methods, yet uses a smaller template size than other multiscale methods.
Description: 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2010, San Francisco, CA, 13-18 June 2010
URI: http://hdl.handle.net/10397/16765
ISBN: 9781424469840
ISSN: 1063-6919
DOI: 10.1109/CVPR.2010.5539909
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