Selective coding of human faces using wavelets

Jaeyoung Seol, Kwanghoon Sohn, Chulhee Lee

Abstract: Proposes an automated selective coding algorithm for human faces using neural networks and wavelets. In the proposed coding algorithm, we try to preserve information about human faces as much as possible without compromising the overall compression efficiency. In particular, we want to eliminate the artifacts near the boundary between the face and the background. We first extract the facial area using the eye location information and the skin color information. When we allocate bits at each level in the wavelet transform, we allocate more bits to the area that corresponds to the facial area. Experiments show that we can obtain a crisper facial area at the expense of the background.