An effective colour feature extraction method using evolutionary computation for face recognition

Peichung Shih, Chengjun Liu

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

This paper presents a colour feature extraction method using a Genetic Algorithm (GA) to seek the optimal colour space transformation that leads to an effective image representation for face recognition. A new colour space, LC1C2, consisting of one luminance (L) channel and two chrominance channels (C1, C2) is introduced as a linear transformation of the input RGB colour space. The specific transformation from the RGB colour space to the LC1C2 colour space is optimised by a GA where a fitness function guides the evolution towards higher recognition accuracy.

Original languageEnglish (US)
Pages (from-to)206-227
Number of pages22
JournalInternational Journal of Biometrics
Volume3
Issue number3
DOIs
StatePublished - Jun 2011

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

Keywords

  • BEE
  • Biometric experimentation environment
  • Colour space
  • FRGC
  • Face recognition grand challenge
  • GAs
  • Gallery
  • Genetic algorithms
  • Probe
  • Query
  • Target

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