A Skin Detection Algorithm Based on Bayes Decision in the YCbCr Color Space
Skin color detection is a hot research of computer vision,pattern identification and human-computer interaction.Skin region is one of the most important features to detect the face and hand pictures.For detecting the skin images effectively,a skin color classification technique that employs Bayesian decision with color statistics data has been presented.In this paper,we have provided the description,comparison and evaluation results of popular methods for skin modeling and detection.A Bayesian approach to skin color classification was presented.The statistics of skin color distribution were obtained in YCbCr color space.Using the Bayes decision rule for minimum cot,the amount of false detection and false dismissal could be controlled by adjusting the threshold value.The results showed that this approach could effectively identify skin color pixels and provide good coverage of all human races,and this technique is capable of segmenting the hands and face quite effectively.The algorithm allows the flexibility of incorporating additional techniques to enhance the results.
Color detection Color segmentation Color space Skin modeling
Xinyan Cao Hongfei Liu
College of Electronic Information Engineering, University of Changchun,Changchun, Jilin Province, 13 College of Transportation, Jilin University, Changchun 130022, China
国际会议
台湾
英文
672-676
2011-12-11（万方平台首次上网日期，不代表论文的发表时间）