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

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.