Palmprint Recognition Based on Sparse Two-Dimensional Local Discriminant Projections

Jian Xin Zhang; Zhang E Zhang; Jian Yang Liu

doi:10.4028/www.scientific.net/AMR.998-999.894

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 998-999Palmprint Recognition Based on Sparse...

Palmprint Recognition Based on Sparse Two-Dimensional Local Discriminant Projections

Abstract:

A novel palmprint recognition method based on sparse two-dimensional local discriminant projections (S2DLDP) is proposed. After a description of the basic theory and resolution method for S2DLDP, the paper presents the detail palmprint feature extraction method based on S2DLDP, and tests the algorithm performance by various non-zero elements size and neighborhood size. S2DLDP considerers the class information, local separability, two-dimensional image inherent properties of training samples and sparse projection, which provides an intuitive, semantic and interpretable feature subspace for palmprint representation. The optimal recognition accuracy of EER=2.2% is obtained on PolyU palmprint database, which also illuminates the effectiveness of the proposed algorithm.

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Periodical:

Advanced Materials Research (Volumes 998-999)

Pages:

894-898

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.998-999.894

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Online since:

July 2014

Authors:

Jian Xin Zhang*, Zhang E Zhang, Jian Yang Liu

Keywords:

2DLPP, Palmprint Recognition, S2DLDP, Sparse Projection

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