Paper Title:
A Novel Method for Palmprint Recognition Based on Tensor Subspace Learning
  Abstract

Recently, palmprint identification has been developed for security purpose. In this paper, we propose a novel palmprint recognition scheme which has three features: 1) representation of palmprint images by Local Binary Pattern (LBP); 2) dimensionality reduction by tensor subspace learning; and 3) recognition by multiple kernel classification method based on tensor analysis. LBP can effectively capture substantial palm features while keeping robustness to illumination. Then we reduce the dimensionality of each palmprint samples based on tensor subspace learning which can preserve the spatial structure of LBP. Tensor multiple kernel SVM classifier is finally employed for palmprint recognition. Experimental results on PolyU palmprint database show the effectiveness of the proposed method.

  Info
Periodical
Key Engineering Materials (Volumes 439-440)
Edited by
Yanwen Wu
Pages
1398-1403
DOI
10.4028/www.scientific.net/KEM.439-440.1398
Citation
Y. L. Xiao, "A Novel Method for Palmprint Recognition Based on Tensor Subspace Learning ", Key Engineering Materials, Vols. 439-440, pp. 1398-1403, 2010
Online since
June 2010
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Price
$32.00
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