By Topic

Face Detection in Color Images Using AdaBoost Algorithm Based on Skin Color Information

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Yanwen Wu ; Huazhong Normal Univ., Wuhan ; Xueyi Ai

This paper proposes a novel technique for detecting faces in color images using AdaBoost algorithm combined with skin color segmentation. First,skin color model in the YCbCr chrominance space is built to segment the non-skin-color pixels from the image. Then, mathematical morphological operators are used to remove noisy regions and fill holes in the skin-color region, so we can extract candidate human face regions. Finally, these face candidates are scanned by cascade classifier based on AdaBoost for more accurate face detection. This system detects human face in different scales, various poses, different expressions, lighting conditions, and orientation. Experimental results show the proposed system obtains competitive results and improves detection performance substantially.

Published in:

Knowledge Discovery and Data Mining, 2008. WKDD 2008. First International Workshop on

Date of Conference:

23-24 Jan. 2008