2014/07/24 by Reza Azad, Azad, Reza, Hamid Reza Shayegh +1
Computer Science · #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Face and Expression Recognition #Video Surveillance and Tracking Methods #cs.CV
paper · pdf · doi:10.48550/arxiv.1407.6506
2013 First International Conference on computer, Information Technology and Digital Media. arXiv admin note: substantial text overlap with arXiv:1407.6318
arxiv created 2014/07/24 · openalex publication_date 2014/07/24 · arxiv updated 2014/07/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Skin detection is one of the most important and primary stages in some of image processing applications such as face detection and human tracking. So far, many approaches are proposed to done this case. Near all of these methods have tried to find best match intensity distribution with skin pixels based on popular color spaces such as RGB, CMYK or YCbCr. Results show these methods cannot provide an accurate approach for every kinds of skin. In this paper, an approach is proposed to solve this problem using statistical features technique. This approach is including two stages. In the first one, from pure skin statistical features were extracted and at the second stage, the skin pixels are detected using HSV and YCbCr color spaces. In the result part, the proposed approach is applied on FEI database and the accuracy rate reached 99.25 + 0.2. Further proposed method is applied on complex background database and accuracy rate obtained 95.40+0.31%. The proposed approach can be used for all kinds of skin using train stage which is the main advantages of it. Low noise sensitivity and low computational complexity are some of other advantages.