Optimized Local Image Watermarking Combining Feature Point and Texture

The textured regions embedded a watermark have better visual quality than the smooth regions in an image. To take advantage of the image texture being easy to hide the watermark, accurately locating the regions in an image with rich texture is significant. This paper proposes an optimized local image watermarking algorithm combining feature point and texture. The SURF feature points extracted from an image with moderate scales are selected to obtain initial watermark embedding regions. A scoring scheme by comprehensively analyzing texture, scale, and position of a region is proposed to evaluate the regions around each initial embedding region, and select the regions with the highest score from them to constitute the candidate embedding regions. Finally, the same watermarks are embedded in multiple non-overlapping embedding regions to guarantee the imperceptibility and improve the robustness. The simulation experiments on 100 images show the superiority of our proposed method compared with the state-of-the-art method in terms of imperceptibility and robustness.