An Intelligent Blind Semi-fragile Watermarking Scheme for Effective Authentication and Tamper Detection of Digital Images Using Curvelet Transforms

A novel intelligent semi-fragile watermarking scheme for authentication and tamper detection of digital images is proposed in this paper. This watermarking scheme involves embedding and extraction of the quantized first level Discrete Curvelet Transform (DCLT) coarse coefficients. The amount of quantization of the first level coarse DCLT coefficients of the input image is decided intelligently based on the energy contribution of the coefficients. At the receiver side, the extracted and generated first level coarse DCLT coefficients of the watermarked image is divided into blocks of uniform size. A feature similarity index value between each block of extracted and generated coefficients is compared and if the difference exceeds threshold, the block is marked as tampered. The watermarking scheme is blind and does not require any additional information to identify authenticity of the watermarked image. Experiments are conducted rigorously and the results reveal that the proposed method is robust than the existing method [1]. Better accuracy in localizing tampered regions is achieved compared to method [1].