Face detection in color images based on skin color models

Li Zou*, Sei Ichiro Kamata

*Corresponding author for this work

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

13 Citations (Scopus)


Face finding is a very important initial step towards building up a fully automated face recognition system. Face detection by detecting skin like colors can achieve a high detection rate. In this paper, we presented a novel algorithm for face detection in color images with complex backgrounds. First a parallel structure for skin color detection is proposed to improve the accuracy of detections. The concept of the probability image has been introduced to utilize the color information in the traditional face detection methods specific for gray-scale images. After that, a classifier obtained from Adaboost training is applied to the result of skin detection to reduce the false positives. An experiment has been implemented to verify the improvement of this proposed research. And the proposed approach achieved a better result in this experiment.

Original languageEnglish
Title of host publicationTENCON 2010 - 2010 IEEE Region 10 Conference
Number of pages6
Publication statusPublished - 2010 Dec 1
Event2010 IEEE Region 10 Conference, TENCON 2010 - Fukuoka, Japan
Duration: 2010 Nov 212010 Nov 24

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON


Other2010 IEEE Region 10 Conference, TENCON 2010


  • Adaboost
  • Face detection
  • Face skin categorization
  • GMM
  • Skin color

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering


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