ADAPTIVE WATERMARKING AND PERFORMANCE ANALYSIS BASED ON IMAGE CONTENT

Abstract

This paper presents a novel adaptive watermarking based on iteration mapping and image content. An original image is divided into non-overlapped blocks, which are analyzed by means of fractal dimension, and the feature blocks which contain edges and textures are further classified by variance characteristics into three different parts: edges, weak textures, and strong textures. The original watermark is a distinguishable gray image, which is scrambled and amended to form a watermark signal to be embedded. DCT is applied to all the original image blocks and the formed watermark is embedded into their middle-frequency coefficients with different strength. Performance analysis of adaptive watermark extraction is presented in details. Experimental results show that this algorithm is able to achieve a watermarked image with good perceptual invisibility, high security and strong robustness.