Face recognition based on binary template matching

Jiatao Song, Beijing Chen, Zheru Chi, Xuena Qiu, Wei Wang

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

9 Citations (Scopus)


In this paper, a novel face recognition method based on binary face edges is presented to deal with the illumination problem. The Binary Face Edge Map (BFEM) is extracted using the Locally Adaptive Threshold (LAT) algorithm. Based on BEFM, a new image similarity metric is proposed. Experimental results show that face recognition rates of 76.32% and 82.67% are achieved respectively on 798 AR images and 150 Yale images with changed lighting conditions and facial expression variations when one sample per subject is used as the target image. The proposed method takes less time for image matching and outperforms some existing face recognition approaches, especially in changed lighting conditions.
Original languageEnglish
Title of host publicationAdvanced Intelligent Computing Theories and Applications
Subtitle of host publicationWith Aspects of Theoretical and Methodological Issues - Third International Conference on Intelligent Computing, ICIC 2007, Proceedings
Number of pages9
Publication statusPublished - 1 Dec 2007
Event3rd International Conference on Intelligent Computing, ICIC 2007 - Qingdao, China
Duration: 21 Aug 200724 Aug 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4681 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference3rd International Conference on Intelligent Computing, ICIC 2007


  • Binary edge map
  • Binary template matching
  • Face recognition
  • Illumination

ASJC Scopus subject areas

  • General Computer Science
  • General Biochemistry,Genetics and Molecular Biology
  • Theoretical Computer Science


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