Skin Colour-Based Face Detection in Colour Images

We propose in this work a method for detecting faces in colour images with complex backgrounds. The approach starts with the transformation of the image pixels from the RGB colour space to the chrominance space (YCbCr). Secondly, a Gaussian model is fitted on the transformed image in order to calculate the likelihood of skin for each pixel and to create a likelihood image. Thirdly, by thresholding the likelihood image, skin pixels are segmented to form a binary skin map, which contains the candidate face regions. Finally, a verification process is carried out to determine whether these candidate face regions are real faces or not.

• Type: Conference
• Year: 2006
• Where: AVSS
• Authors: Wen-Hsiang Lai, Chang-Tsun Li
• Keywords: AVSS 2006, Candidate Face Regions, Image, Likelihood Image, Signal Processing