Face Recognition in Color Images Based on Skin Color Evidence

This paper show cases a novel procedures for detecting faces in color images using combine with skin color segmentation. First, skin color model in the YCbCr chrominance space is built to segment the non-skin-color pixels from the image. Then, mathematical morphological operators are used to remove noisy regions and fill holes in the skin-color region, so we can extract applicant human face regions. Finally, these face applicants are scanned by Cascade classifier based on AdaBoost for more meticulous face detection. This system perceives human face in different scales, various postures, different utterance, lighting conditions, and assimilation. Exploratory results show the proposed system obtains competitive results and improves detection appearance significantly.