Affiliations: School of Computer and Information Technology, Liaoning Normal University, Dalian, China. wxy37@126.com
Note: [] This work was supported by the National Natural Science Foundation of China under Grant No. 61272416, 60773031 & 60873222, the Open Project Program of Jiangsu Key Laboratory of Image and Video Understanding for Social Safety (Nanjing University of Science and Technology) under Grant No. JSKL201303, and Liaoning Research Project for Institutions of Higher Education of China under Grant No. 2008351 & L2010230. Also works: Jiangsu Key Laboratory of Image and Video Understanding for Social Safety, Nanjing University of Science and Technology, Nanjing, 210094, P.R. China Address for correspondence: Liaoning Normal University, Dalian, China
Abstract: Robust digital watermarking has been an active research topic in the last decade. As one of the promising approaches, feature point based image watermarking has attracted many researchers. However, the related work usually suffers from the following limitations: 1) The feature point detector is sensitive to texture region, and some noise feature points are always detected in the texture region. 2) The feature points focus too much on high contrast region, and the feature points are distributed unevenly. Based on Bayesian image segmentation, we propose a local geometrically invariant image watermarking scheme with good visual quality in this paper. Firstly, the Bayesian image segmentation is used to segment the host image into several homogeneous regions. Secondly, for each homogeneous region, image feature points are extracted using the multiscale Harris-Laplace detector, and the corresponding invariant local image regions are constructed adaptively. Finally, by taking the human visual system (HVS) into account, digital watermark is repeatedly embedded into local image regions by modulating the magnitudes of DFT coefficients. By binding the digital watermark with the invariant local image regions, the watermark detection can be done without synchronization error. Experimental results show that the proposed image watermarking is not only invisible and robust against common image processing operations such as sharpening, noise adding, and JPEG compression etc, but also robust against the geometric distortions.
Keywords: Image watermarking, geometric distortion, Bayesian image segmentation, local image region, human visual system
