¹School of Computer Science, Wuhan Textile University, Wuhan 430073, China
²Department of Computer Science, Georgia State University, Atlanta 30303, USA
³Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan 430074, China
⁴College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China

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Abstract—An effective and integrated image watermarking scheme mainly includes watermark generation, watermark embedding, watermark identification, and watermark attack. In this paper, a novel discrete wavelet transform domain image watermark scheme is proposed to meet the watermarking properties: security, imperceptibility and robustness. Here watermark comes from a meaningful binary image encrypted by two-dimensional chaotic stream encryption, which has more security. In the procedure of watermark embedding, the watermark is embedded into host image through selecting and modifying the wavelet coefficients using genetic algorithms with a simple fitness function to improve the imperceptibility of watermarked image. In order to identify the owner of extracted watermark, synergetic neural networks are used in the watermarking identification to overcome the limitation of correlation analysis or the human sense organ after some attacks. The results of our scheme realization and robust experiments show that this scheme has preferable performance.

Index Terms—image watermark, genetic algorithm, synergetic neural networks, discrete wavelet transform

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Cite: Chen Yongqiang, Zhang Yanqing, Hu Hanping, Ling Hefei, "A Novel Gray Image Watermarking Scheme," Journal of Software vol. 6, no. 5, pp. 849-856, 2011.