Person recognition by fusing palmprint and palm vein images based on "Laplacianpalm" representation

  • Authors:

  • Jian-Gang Wang;Wei-Yun Yau;Andy Suwandy;Eric Sung

  • Affiliations:

  • Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore;Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore;Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613, Singapore;Nanyang Technological University, Singapore 639798, Singapore

  • Venue:
  • Pattern Recognition
  • Year:
  • 2008

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Abstract

Unimodal analysis of palmprint and palm vein has been investigated for person recognition. One of the problems with unimodality is that the unimodal biometric is less accurate and vulnerable to spoofing, as the data can be imitated or forged. In this paper, we present a multimodal personal identification system using palmprint and palm vein images with their fusion applied at the image level. The palmprint and palm vein images are fused by a new edge-preserving and contrast-enhancing wavelet fusion method in which the modified multiscale edges of the palmprint and palm vein images are combined. We developed a fusion rule that enhances the discriminatory information in the images. Here, a novel palm representation, called ''Laplacianpalm'' feature, is extracted from the fused images by the locality preserving projections (LPP). Unlike the Eigenpalm approach, the ''Laplacianpalm'' finds an embedding that preserves local information and yields a palm space that best detects the essential manifold structure. We compare the proposed ''Laplacianpalm'' approach with the Fisherpalm and Eigenpalm methods on a large data set. Experimental results show that the proposed ''Laplacianpalm'' approach provides a better representation and achieves lower error rates in palm recognition. Furthermore, the proposed multimodal method outperforms any of its individual modality.