Region-based and content adaptive skin detection in color images

Wei Che Chen, Ming Shi Wang

Research output: Contribution to journalArticle

9 Citations (Scopus)


Skin detection plays an important role in applications such as face detection and tracking, person detection and pornography detection. While previous studies focus on pixel-based skin color detection techniques that individually classify each pixel as skin color or non-skin color, this study presents a region-based algorithm for detecting skin color. The proposed algorithm uses a special region, called key skin region, as the basis to classify skin color. A performance comparison with conventional skin classifiers, including the Bayesian classifier, the unimodal Gaussian classifier and the Gaussian mixture classifier, is made in this study. Experimental results show that the proposed algorithm outperforms other tested skin classifiers. Furthermore, the skin regions detected by the proposed algorithm, especially facial regions, are nearly complete with no hollow holes in these regions. This property can simplify the complexity of implementing applications that use skin color as their basis, such as face detection and face tracking.

Original languageEnglish
Pages (from-to)831-853
Number of pages23
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Issue number5
Publication statusPublished - 2007 Aug 1

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Region-based and content adaptive skin detection in color images'. Together they form a unique fingerprint.

  • Cite this