By Topic

Face detection using 2D-Discrete Cosine Transform and Back Propagation Neural Network

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)
Tayyab, M. ; Dept. of EE, Int. Islamic Univ., Islamabad, Pakistan ; Zafar, M.F.

Human brain can detect faces from the images constructed in their eyes. The face detection is a computerize method of locating the face in the digital image. It is an important challenge to locate faces from uncontrolled and indistinguishable background of the digital image. This paper presents human face detection from the colored images. Skin color segmentation is used for localizations of skin colored components in the digital image. The features are extracted by using 2D-Discrete Cosine Transform (2D-DCT) and the Back Propagation Neural Network (BPN) is used for training and testing phases. In this research, total of 50, 100 and 180 images datasets have been used. About 60% of the images are used for training phase and 40% of the images are used for testing phase. The detection rate has been obtained as 84.03% with the false rate of 5.05. These results are better than the results of existing methods of face detection using 2D-DCT.

Published in:

Emerging Technologies, 2009. ICET 2009. International Conference on

Date of Conference:

19-20 Oct. 2009