Extracting faces and facial features from color images

Frank Y. Shih, Shouxian Cheng, Chao Fa Chuang, Patrick S.P. Wang

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

In this paper, we present image processing and pattern recognition techniques to extract human faces and facial features from color images. First, we segment a color image into skin and non-skin regions by a Gaussian skin-color model. Then, we apply mathematical morphology and region filling techniques for noise removal and hole filling. We determine whether a skin region is a face candidate by its size and shape. Principle component analysis (PCA) is used to verify face candidates. We create an ellipse model to locate eyes and mouths areas roughly, and apply the support vector machine (SVM) to classify them. Finally, we develop knowledge rules to verify eyes. Experimental results show that our algorithm achieves the accuracy rate of 96.7% in face detection and 90.0% in facial feature extraction.

Original languageEnglish (US)
Pages (from-to)515-534
Number of pages20
JournalInternational Journal of Pattern Recognition and Artificial Intelligence
Volume22
Issue number3
DOIs
StatePublished - May 2008

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

Keywords

  • Face extraction
  • Facial feature
  • Mathematical morphology
  • Principle component analysis
  • Support vector machine

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