Skin detection using a Markov random field and a new color space

K. Chenaoua*, A. Bouridane

*Corresponding author for this work

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

19 Scopus citations

Abstract

In this paper, human skin detection is performed using a new color space coordinate and a Markov random field based approach. The proposed color space uses a variant of the principal component analysis technique to reduce the number of color components. The MRF model takes into account the spatial relations within the image that are included in the labeling process through statistical dependence among neighboring pixels. Since only two classes are considered the Ising model is used to perform the skin/non-skin classification process.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Image Processing, ICIP 2006 - Proceedings
Pages2673-2676
Number of pages4
DOIs
StatePublished - 2006

Publication series

NameProceedings - International Conference on Image Processing, ICIP
ISSN (Print)1522-4880

Keywords

  • MRF
  • PCA
  • PFA
  • Skin detection

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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