Affiliations: School of Computer and Information Technology, Liaoning Normal University, Dalian 116029, P.R. China. wxy37@126.com; yhy_65@126.com
Note: [] This work was supported by the National Natural Science Foundation of China under Grant No. 61272416, 60873222, & 60773031, and 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. 30920130122006, the Open Foundation of Zhejiang Key Laboratory for Signal Processing under Grant No. ZJKL_4_SP-OP2013-01, and Liaoning Research Project for Institutions of Higher Education of China under Grant No. L2013407. Also works: Jiangsu Key Laboratory of Image and Video Understanding for Social Safety, Nanjing University of Science and Technology Nanjing, 210094, P. R. China.
Note: [] Address for correspondence: School of Computer and Information Technology, Liaoning Normal University, Dalian, P.R. China.
Abstract: Geometric distortions that cause displacement between embedding and detection are usually difficult for watermark to survive. It is a challenging work to design a robust image watermarking scheme against geometric distortions, especially for local geometric distortions. Based on probability density and complex angular radial transform theory, a new image watermarking algorithm robust to geometric distortions is proposed in this paper. We firstly extract the steady image feature points by using new image feature point detector, which is based on the probability density. Then we build the affine invariant local feature regions based on probability density auto-correlation matrix. And finally, we present a new image watermarking algorithm robust to geometric distortions, in which the digital watermark is embedded into the local complex angular radial transform (CART) coefficients. Experiments results show that the proposed image watermarking is not only invisible and robust against common image processing operations, but also robust against the geometric distortions.
