Image and Graphics

In this paper, we introduce the sparse two-dimensional local discrim‐ inant projections (S2DLDP) algorithm into palmprint recognition, and give an exactly recognition performance evaluation of the S2DLDP algorithm on public PolyU palmprint database. S2DLDP algorithm applies the idea of sparse for 2DLDP, possessing advantages of high computational efficiency and recognition performance. We perform the algorithm using various non-zero elements and image sizes, and then compare it with LDA, LPP and DLPP algorithm. The optimal recognition rate obtained by S2DLDP is 99.5%, which is significantly higher than the other three methods. Experiment results illuminate the excellent effectiveness of the S2DLDP algorithm for palmprint recognition.

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