Mohd Zamri Osman and Mohd Aizaini Maarof and Mohd Foad Rohani
Towards Integrating Statistical Color Features for Human Skin Detection
317 - 321
2016
10
2
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/10003677
https://publications.waset.org/vol/110
World Academy of Science, Engineering and Technology
Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixelbased does not eliminate the skinlike color due to the intensity of skin and skinlike color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1score 0.969.
Open Science Index 110, 2016