Holistic orthogonal analysis of discriminant transforms for color face recognition

Xiaoyuan Jing, Qian Liu, Chao Lan, Jiangyue Man, Sheng Li, Dapeng Zhang

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

16 Citations (Scopus)


The key of color face recognition technique is how to effectively utilize the complementary information between color components and remove their redundancy. Present color face recognition methods generally reduce the correlations between color components in the image pixel level, and then extract the discriminant features from the uncorrelated color face images. In this paper, we propose a novel color face recognition approach based on the holistic orthogonal analysis (HOA) of discriminant transforms of color images. HOA can reduce the correlation of color information in the feature level. It in turn achieves the discriminant transforms of red, green and blue color images by using the Fisher criterion, and simultaneously makes the achieved transforms mutually orthogonal. Experimental results on the AR and FRGC-2 public color face image databases demonstrate that the proposed approach acquires better recognition performance than several representative color face recognition methods.
Original languageEnglish
Title of host publication2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
Number of pages4
Publication statusPublished - 1 Dec 2010
Event2010 17th IEEE International Conference on Image Processing, ICIP 2010 - Hong Kong, Hong Kong
Duration: 26 Sep 201029 Sep 2010


Conference2010 17th IEEE International Conference on Image Processing, ICIP 2010
Country/TerritoryHong Kong
CityHong Kong


  • Color face recognition
  • Discriminant transforms
  • Feature extraction
  • Holistic orthogonal analysis

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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