원문정보
초록
영어
Skin color detection is the process that classifies unknown colors into skin or non-skin classes. Skin color detection is preliminary step for facial or gesture analysis and can reduce search space for next higher level processing. In this paper, we show that proposed PCA-based color representation can give better performance than other frequently used color spaces such as XYZ and Luv. For skin detection, we use two classification models – histogram model and elliptical boundary model from skin and non-skin colors. The experimental results show the PCA-based color representation is more efficient than other color representation and the existing PCA-based representation based on the two classification models.
목차
1. Introduction
2. Effectiveness of PCA-based Color Representation on Skin Color Detection
2.1. PCA on Color Vectors
2.2. Luminance and Chrominance Separation based on PCA
3. Skin Color Detection based on Histogram Model
4. Skin Color Detection based on Elliptical Boundary Model
5. Experimental Results
6. Conclusion
Acknowledgements
References