Is white light the best illumination for palmprint recognition?

Zhenhua Guo, Dapeng Zhang, Lei Zhang

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 Citations (Scopus)

Abstract

Palmprint as a new biometric has received great research attention in the past decades. It owns many merits, such as robustness, low cost, user friendliness, and high accuracy. Most of the current palmprint recognition systems use an active light to acquire clear palmprint images. Thus, light source is a key component in the system to capture enough of discriminant information for palmprint recognition. To the best of our knowledge, white light is the most widely used light source. However, little work has been done on investigating whether white light is the best illumination for palmprint recognition. In this study, we empirically compared palmprint recognition accuracy using white light and other six different color lights. The experiments on a large database show that white light is not the optimal illumination for palmprint recognition. This finding will be useful to future palmprint recognition system design.
Original languageEnglish
Title of host publicationComputer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings
Pages50-57
Number of pages8
DOIs
Publication statusPublished - 28 Sept 2009
Event13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009 - Munster, Germany
Duration: 2 Sept 20094 Sept 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5702 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009
Country/TerritoryGermany
CityMunster
Period2/09/094/09/09

Keywords

  • (2D) PCA 2
  • Biometrics
  • Illumination
  • Palmprint recognition

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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