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First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008)
Face Detection in Color Images Using AdaBoost Algorithm Based on Skin Color Information
Adelaide, Australia
January 23-January 24
ISBN: 0-7695-3090-7
This paper proposes a novel technique for detecting faces in color images using AdaBoost algorithm combined 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 candidate human face regions. Finally,these face candidates are scanned by cascade classifier based on AdaBoost for more accurate face detection. This system detects human face in different scales, various poses, different expressions, lighting conditions, and orientation. Experimental results show the proposed system obtains competitive results and improves detection performance substantially.
Citation:
Yanwen Wu, Xueyi Ai, "Face Detection in Color Images Using AdaBoost Algorithm Based on Skin Color Information," wkdd, pp.339-342, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008
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