Feature-level fusion for effective palmprint authentication

Adams Wai Kin Kong, Dapeng Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

74 Citations (Scopus)

Abstract

A feature-level fusion approach is proposed for improving the efficiency of palmprint identification. Multiple Gabor filters are employed to extract the phase information on a palmprint image, which is then merged according to a fusion rule to produce a single feature called the Fusion Code. The similarity of two Fusion Codes is measured by their normalized hamming distance. A database containing 7,752 palmprint images from 386 different palms is used to validate the performance of the proposed method. Empirically comparing our previous non-fusion approach and the proposed method, improvement in verification is ensured.
Original languageEnglish
Pages (from-to)761-767
Number of pages7
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3072
Publication statusPublished - 1 Dec 2004

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this