Earticle

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

Abstract
 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

키워드

저자

• Sungyoung Kim [ Dept. Computer Engineering, Kumoh National Institute of Techonogy, Daehak-ro 61, Gumi, Gyeongbuk 730-701, Korea ]
• JaepilKo [ Dept. Computer Engineering, Kumoh National Institute of Techonogy, Daehak-ro 61, Gumi, Gyeongbuk 730-701, Korea ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605