Face recognition based on binary images for link selection

Sanghun Lee, Soochang Kim, Young Hoon Kim, Chulhee Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A face recognition system which utilizes binary facial images and a bitwise similarity calculation method is proposed for link selection between mobile devices. As a pre-processing step, normalized differences of Gaussian and facial region estimation were used to handle illumination conditions. Binary images were used to extract facial feature sets that did not exceed 700 bytes. Scale pyramids and XNOR+AND similarity scores were used for fast feature matching between reference data sets and pre-processed test data. The proposed method achieved about an 85.9% recognition rate with a database that consisted of 135 facial images with various head poses, obtained by enrolling one reference data set per subject.

Original languageEnglish
Title of host publicationVISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications
PublisherSciTePress
Pages589-593
Number of pages5
ISBN (Print)9789897580048
DOIs
Publication statusPublished - 2014
Event9th International Conference on Computer Vision Theory and Applications, VISAPP 2014 - Lisbon, Portugal
Duration: 2014 Jan 52014 Jan 8

Publication series

NameVISAPP 2014 - Proceedings of the 9th International Conference on Computer Vision Theory and Applications
Volume2

Other

Other9th International Conference on Computer Vision Theory and Applications, VISAPP 2014
Country/TerritoryPortugal
CityLisbon
Period14/1/514/1/8

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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