Finding and Segmenting Human Faces

Detta är en Master-uppsats från Uppsala universitet/Institutionen för informationsteknologi

Författare: Qing Gu; [2008]

Nyckelord: ;


Human face and facial feature detection have attracted a lot of attention because of their wide applications, such as face recognition, face image database management and human-computer interaction. So it is of interest to develop a fast and robust algorithm to detect the human face and facial features. This paper is about a study of finding faces within images and segmenting the face into numbered regions which are the face-, mouth-, eyes- and hair regions respectively. In the last few years, many face detection methods have been proposed based on different specific conditions. The detection system in this master thesis project is implemented using color images with complex backgrounds under various lighting conditions. Each input image is dominated by the upper half of a single person. The algorithm presented in the paper uses a combined algorithm to detect the face. First, a skin color detection algorithm is applied to detect the four possible face regions. Second, the algorithm locates eyes within the candidate regions, and then the region with eyes becomes the face region. Finally, the algorithm locates the mouth and hair from the eyes and face regions.

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