Robust Digital Image Watermarking Scheme with Neural Network and Fuzzy Logic Approach

The copyright protection of digital content became a critical issue nowadays. Digital image watermarking is one of the techniques used to protect digital content. In this paper two novel approaches are compared to embed watermark into the host image using quantization based on Back Propagation Neural Network (BPNN), and Dynamic Fuzzy Inference System (DFIS). The cover image is decomposed up to 3-levels using quantization and DWT. The bitmap is selected as a watermark. The back propagation neural network is implemented to embed and extract the watermark in one method, while the DFIS is utilized to generate the watermark weighting function to embed& extract the imperceptible watermark in the other method The proposed watermarking algorithms are imperceptible and robust to some normal attacks such as JPEG compression, salt and pepper noise, median filtering, rotation, and cropping. Keywords—Watermark, Quantization, DWT, Back Propagation Neural Network, Bitmap, Dynamic Fuzzy Inference System, Imperceptible, Robust, JPEG Compression, Cropping.