Face region detection using DCT and homomorphic filter
Kyunghwan Baek, Yeongsoo Chang, Daeuong Kim, Young-Tak Kim, Boo-Hyoung Lee, Hwanik Chung, Youngjoon Han, Hernsoo Hahn · 2007
Abstract:- This paper proposes a new approach for the detection of face regions where the facial features such as eyes, nose, and mouth may exist with very high probability. It uses the characteristic of DCT(discrete cosine transformation) that concentrates the energy of an image into lower frequency coefficients. Since the facial features are pertained to relatively high frequency in a face image, the inverse DCT after removing the DCT's coefficients corresponding to the lower frequencies generates the image where the facial feature regions are emphasized. For an efficient application of the proposed method, homomorphic filter is used with the global contrast factor. The DCT coefficients are eliminated so that the global contrast factor can be maximized. Once the inverse DCTed image is obtained, the face region is found by analyzing the topology of facial features. The proposed algorithm has been tested with various images collected randomly. The experimental results have shown a superior performance even when an image has a complex background.