Extraction and Cross-Matching of Palm-Vein and Palmprint from the RGB and the NIR Spectrums for Identity Verification

Sungchul Cho, Beom Seok Oh, Kar Ann Toh, Zhiping Lin

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this paper, we propose a novel cross-spectral matching system for identity verification based on the palm-vein and the palmprint acquired from the visible (RGB) and the near infrared (NIR) image spectral bands. Considering the vast availability of the visible library, the red and the blue spectrums are treated as sources of gallery samples and the NIR spectral band is utilized as the probe source without loss of generality. Apart from the extraction of palm-vein and palmprint features, the discriminative power of the palmprint templates is enhanced using a simplified Local Binary Pattern (LBP) encoding scheme. The similarity scores obtained by matching the NIR palm-vein templates against the registered RGB palm-vein templates is finally fused with scores obtained from matching the NIR palmprint codes against the registered RGB palmprint codes. Our empirical results on two publicly available multi-spectral palm databases show that the proposed system consistently achieves promising verification performance.

Original languageEnglish
Article number8945316
Pages (from-to)4005-4021
Number of pages17
JournalIEEE Access
Volume8
DOIs
Publication statusPublished - 2020 Jan 1

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

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