Face recognition based on modified LBP

Zhigang Zhang, Xiangjian He

Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

Abstract

Face recognition in unconstrained, natural conditions still remains a challenging task. As a powerful local descriptor, Local Binary Patterns has shown the advantage of representation and performance. However, it is still affected by robustness and accuracy. In this paper, a novel method is presented to improve the performance of automatic face recognition under uncontrolled conditions. We modify the conventional Local Binary Pattern and use it as a new feature descriptor. Partial Hausdorff Distance is applied as a dissimilarity measurement. Experimental results show that the proposed algorithm outperforms the traditional LBP approach in terms of accuracy rate and robustness. It can reduce the sensitivity caused by illumination variation, pose variation, occlusion etc.

Original languageEnglish
Title of host publicationICCSE 2012 - Proceedings of 2012 7th International Conference on Computer Science and Education
Pages160-164
Number of pages5
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 7th International Conference on Computer Science and Education, ICCSE 2012 - Melbourne, VIC, Australia
Duration: 14 Jul 201217 Jul 2012

Publication series

NameICCSE 2012 - Proceedings of 2012 7th International Conference on Computer Science and Education

Conference

Conference2012 7th International Conference on Computer Science and Education, ICCSE 2012
Country/TerritoryAustralia
CityMelbourne, VIC
Period14/07/1217/07/12

Keywords

  • face recognition
  • local binary patterns
  • partial hausdorff distance

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Theoretical Computer Science

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