Face segmentation using skin-color map in videophone applications

• Published in: IEEE transactions on circuits and systems for video technology Vol. 9; no. 4; pp. 551 - 564
• Main Authors: Chai, D., Ngan, K.N.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.06.1999; Institute of Electrical and Electronics Engineers
• Subjects: Algorithms; Applied sciences; Color; Exact sciences and technology; Face detection; Face recognition; Facial animation; Humans; Image coding; Image processing; Image segmentation; Information, signal and communications theory; Layout; MPEG 4 Standard; Pixels; Segmentation; Segments; Signal processing; Skin; Spatial distribution; Telecommunications and information theory; Video coding; Videophones; Image analysis; Luminance; Spatial distribution; Segmentation; Image processing; Skin color; Coding circuit; Video signal; Fast algorithm; Color image; Facial expression; Videophone
• ISSN: 1051-8215; 1558-2205
• DOI: 10.1109/76.767122

This paper addresses our proposed method to automatically segment out a person's face from a given image that consists of a head-and-shoulders view of the person and a complex background scene. The method involves a fast, reliable, and effective algorithm that exploits the spatial distribution characteristics of human skin color. A universal skin-color map is derived and used on the chrominance component of the input image to detect pixels with skin-color appearance. Then, based on the spatial distribution of the detected skin-color pixels and their corresponding luminance values, the algorithm employs a set of novel regularization processes to reinforce regions of skin-color pixels that are more likely to belong to the facial regions and eliminate those that are not. The performance of the face-segmentation algorithm is illustrated by some simulation results carried out on various head-and-shoulders test images. The use of face segmentation for video coding in applications such as videotelephony is then presented. We explain how the face-segmentation results can be used to improve the perceptual quality of a videophone sequence encoded by the H.261-compliant coder.