Palm-Vein recognition using RGB images

Sungchul Cho, Kar Ann Toh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper addresses the problem of palm-vein recognition based on the RGB color images. Comparing with existing palm-vein methods based on the infrared (IR) or near-infrared (NIR) images, this is the first study of palm-vein recognition utilizing the RGB images. The proposed system consists of three processing steps namely, image enhancement, vein region detection, and feature matching. Essentially, the image enhancement step emphasizes the contrast of the palm-veins for visibility. The lines of the palm-veins are subsequently detected using a simplified Gabor filter which is followed by a binarization for noise removal. Finally, the extracted binary templates are matched using the hamming distance. The system shows an equal error rate of 0.87% on the publicly available PolyU database which consists of four channels: Red, Green, Blue and NIR. This result establishes the feasibility of using the RGB images for palm-vein recognition.

Original languageEnglish
Title of host publicationProceedings of 2018 3rd International Conference on Biomedical Signal and Image Processing, ICBIP 2018
PublisherAssociation for Computing Machinery
Pages47-52
Number of pages6
ISBN (Electronic)9781450364362
DOIs
Publication statusPublished - 2018 Aug 22
Event3rd International Conference on Biomedical Signal and Image Processing, ICBIP 2018 - Seoul, Korea, Republic of
Duration: 2018 Aug 222018 Aug 24

Publication series

NameACM International Conference Proceeding Series

Other

Other3rd International Conference on Biomedical Signal and Image Processing, ICBIP 2018
CountryKorea, Republic of
CitySeoul
Period18/8/2218/8/24

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All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

Cite this

Cho, S., & Toh, K. A. (2018). Palm-Vein recognition using RGB images. In Proceedings of 2018 3rd International Conference on Biomedical Signal and Image Processing, ICBIP 2018 (pp. 47-52). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3278229.3278239