AUTOMATIC FACE REGION WATERMARKING USING QUALIFIED SIGNIFICANT WAVELET TREES

In this paper, a fully automatic scheme for hiding digital watermarks into face regions is proposed. To achieve this goal, an adaptive two-dimensional Gaussian model of skin color distribution is initially used in order to detect face regions within the initial image. Next each face region is decomposed into three levels with ten subbands, using the Discrete Wavelet Transform (DWT) and three pairs of subbands are formed (HL3, HL2), (LH3, LH2) and (HH3, HH2). Afterwards Qualified Significant Wavelet Trees (QSWTs), which are derived from the Embedded Zerotree Wavelet (EZW) algorithm and they are high-energy coefficient paths, are estimated for a pair of subbands. Finally visually recognizable watermark patterns are redundantly embedded to the coefficients of the highest energy QSWTs and the IDWT is applied to provide the watermarked face area. Performance of the proposed face region watermarking system is tested under various signal distortions such as JPEG lossy compression, sharpening and blurring. Experimental results on real life images indicate the efficiency and robustness of the proposed scheme.