Framework for robust blind image watermarking based on classification of attacks

With the widespread internet usage, digital contents are easily distributed throughout the world. To eliminate concerns of producers and owners of digital contents, watermarking techniques are extensively being used. Robustness against intentional and unintentional attacks is a major quality of watermarking systems. Since different attacks tend to target different parts of the frequency spectrum, in this paper we propose a framework for blind watermarking which determines the type of attack that the image has gone through before extracting the watermark. Within this framework, we propose an attack classification method to identify the region of the frequency spectrum that is less damaged. The watermark which is redundantly spread throughout the spectrum can be extracted from the less damaged regions. Experimental results show functionality of the framework by producing better results in comparison with well-known blind watermarking techniques.