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In this paper, we propose a new method for damaging and destroying robust invisible watermarks using an image resizing technique which is named seam carving. By using this method we are able to resize watermarked images in a content-aware manner so that the synchronization of the embedder and extractor of watermarking system is broken and the watermark detection becomes impossible. In contrast to the available benchmarks like Stirmark, proposed attack does not severely reduce the quality of the watermarked image. Therefore it maintains the commercial value of the watermarked image. We have tested the proposed method to attack 3 recent and robust watermarking methods and the results sound... 

In this paper, we used image inpainting as a means for reconstruction of small damaged portions of a watermarked image so that the hidden watermark is not detectable afterwards. Our new watermarking attack algorithm extends the exemplar-based inpainting method, and then we apply it to intended noisy watermarked images to alter the watermark detection process. Our approach is completely free from any pre-assumption on the watermarking algorithm or any other parameters that is used during the watermark embedding procedure. The average PSNR/SSIM of the watermarked image after applying the proposed attack is more than 35/0.98 and the average NC for extracted watermark is lowers than 0.5, so... 

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.... 

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.... 

In this paper, we proposed a categorization for most of the existing watermarking algorithms that work in wavelet domain. Then an adaptive watermarking attack for digital images that is based on the proposed categorization is presented. This attack determines the flat regions, edges and textures of the watermarked image and based on known features of each region the proposed attack tries to destroy the watermark information by manipulating the wavelet coefficients of each region separately such that the least visual distortion will be imposed on the attacked image. We have tested the proposed method to attack two recent and robust watermarking methods and the results sound impressive. The... 

We propose a new nonblind multiresolution watermarking method for still images based on the contourlet transform (CT). In our approach, the watermark is a grayscale image which is embedded into the highest frequency subband of the host image in its contourlet domain. We demonstrate that in comparison to other methods, this method enables us to embed more amounts of data into the directional subbands of the host image without degrading its perceptibility. The experimental results show robustness against several common watermarking attacks such as compression, adding noise, filtering, and geometrical transformations. Since the proposed approach can embed considerable payload, while providing... 

This paper presents an efficient scheme for blind watermark attacking using the concept of matching of the long-range data. The main idea of the proposed attack is to add plenty of noise to the watermarked image and then try to restore an unwatermarked copy of the noisy image. The aim is to destroy the watermark information without accessing the parameters used during the watermark embedding process. So, it allows our approach to be completely free from any pre-assumption on the watermarking algorithm or any other parameters that is used during the watermark embedding procedure. Experimental results show the proposed algorithm's superiority over several other traditional watermarking... 

Along with the improvement of image watermarking techniques, the necessity for effectively and comprehensively evaluating various algorithms becomes imperative. In this paper, we first propose a new categorization that fits for most of the existing watermarking algorithms that work in the wavelet domain. Then an adaptive watermarking attack for evaluating the robustness of watermarking schemes that are based on the proposed categorization is presented. This attack determines the flat regions, edges, and textures of the watermarked image and based on known features of each region the proposed attack tries to destroy the watermark information. This is done by separately manipulating the... 

In this paper, we propose a new multiresolution watermarking method for still images based on the Contourlet Transform (CT). In our algorithm, the watermark is a grayscale image which is embedded into the host image in its contourlet domain. We demonstrate that in comparison with other methods, the proposed method enables us to embed more amount of data into the host image without degrading its perceptual quality. The experimental results show robustness against several common watermarking attacks such as compression, adding noise, and filtering. ©2009 IEEE