Differential feature analysis for palmprint authentication

Xiangqian Wu, Kuanquan Wang, Yong Xu, Dapeng Zhang

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

2 Citations (Scopus)


Palmprint authentication is becoming one of the most important biometric techniques because of its high accuracy and ease to use. The features on palm, including the palm lines, ridges and textures, etc., are resulted from the gray scale variance of the palmprint images. This paper characterizes these variance using different order differential operations. To avoid the effect of the illumination variance, only the signs of the pixel values of the differential images are used to encode palmprint to form palmprint differential code (PDC). In matching stage, normalized Hamming distance is employed to measure the similarity between different PDCs. The experimental results demonstrate that the proposed approach outperforms the existing palmprint authentication algorithms in terms of the accuracy, speed and storage requirement and the differential operations may be considered as one of the standard methods for palmprint feature extraction.
Original languageEnglish
Title of host publicationComputer Analysis of Images and Patterns - 13th International Conference, CAIP 2009, Proceedings
Number of pages8
Publication statusPublished - 28 Sep 2009
Event13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009 - Munster, Germany
Duration: 2 Sep 20094 Sep 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


Conference13th International Conference on Computer Analysis of Images and Patterns, CAIP 2009

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)


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