Towards Optimal Copyright Protection Using Neural Networks Based Digital Image Watermarking

In the field of digital watermarking, digital image watermarking for copyright protection has attracted a lot of attention in the research community. Digital watermarking contains varies techniques for protecting the digital content. Among all those techniques,Discrete Wavelet Transform (DWT) provides higher image imperceptibility and robustness. Over the years, researchers have been designing watermarking techniques with robustness in mind, in order for the watermark to be resistant against any image processing techniques. Furthermore, the requirements of a good watermarking technique includes a tradeoff between robustness, image quality (imperceptibility) and capacity. In this paper, we have done an extensive literature review for the existing DWT techniques and those combined with other techniques such as Neural Networks. In addition to that, we have discuss the contribution of Neural Networks in copyright protection. Finally we reached our goal in which we identified the research gaps existed in the current watermarking schemes. So that, it will be easily to obtain an optimal techniques to make the watermark object robust to attacks while maintaining the imperceptibility to enhance the copyright protection

OR-Benchmark: An Open and Reconfigurable Digital Watermarking Benchmarking Framework

Benchmarking digital watermarking algorithms is not an easy task because different applications of digital watermarking often have very different sets of requirements and trade-offs between conflicting requirements. While there have been some general-purpose digital watermarking benchmarking systems available, they normally do not support complicated benchmarking tasks and cannot be easily reconfigured to work with different watermarking algorithms and testing conditions. In this paper, we propose OR-Benchmark, an open and highly reconfigurable general-purpose digital watermarking benchmarking framework, which has the following two key features: 1) all the interfaces are public and general enough to support all watermarking applications and benchmarking tasks we can think of; 2) end users can easily extend the functionalities and freely configure what watermarking algorithms are tested, what system components are used, how the benchmarking process runs, and what results should be produced. We implemented a prototype of this framework as a MATLAB software package and demonstrate how it can be used in three typical use cases. The first two use cases show how easily we can define benchmarking profiles for some robust image watermarking algorithms. The third use case shows how OR-Benchmark can be configured to benchmark some image watermarking algorithms for content authentication and self-restoration, which cannot be easily supported by other digital watermarking benchmarking systems

Digital watermarking : applicability for developing trust in medical imaging workflows state of the art review

Medical images can be intentionally or unintentionally manipulated both within the secure medical system environment and outside, as images are viewed, extracted and transmitted. Many organisations have invested heavily in Picture Archiving and Communication Systems (PACS), which are intended to facilitate data security. However, it is common for images, and records, to be extracted from these for a wide range of accepted practices, such as external second opinion, transmission to another care provider, patient data request, etc. Therefore, confirming trust within medical imaging workflows has become essential. Digital watermarking has been recognised as a promising approach for ensuring the authenticity and integrity of medical images. Authenticity refers to the ability to identify the information origin and prove that the data relates to the right patient. Integrity means the capacity to ensure that the information has not been altered without authorisation. This paper presents a survey of medical images watermarking and offers an evident scene for concerned researchers by analysing the robustness and limitations of various existing approaches. This includes studying the security levels of medical images within PACS system, clarifying the requirements of medical images watermarking and defining the purposes of watermarking approaches when applied to medical images

Three layer authentications with a spiral block mapping to prove authenticity in medical images

Digital medical image has a potential to be manipulated by unauthorized persons due to advanced communication technology. Verifying integrity and authenticity have become important issues on the medical image. This paper proposed a self-embedding watermark using a spiral block mapping for tamper detection and restoration. The block-based coding with the size of 3x3 was applied to perform selfembedding watermark with two authentication bits and seven recovery bits. The authentication bits are obtained from a set of condition between sub-block and block image, and the parity bits of each sub-block. The authentication bits and the recovery bits are embedded in the least significant bits using the proposed spiral block mapping. The recovery bits are embedded into different sub-blocks based on a spiral block mapping. The watermarked images were tested under various tampered images such as blurred image, unsharp-masking, copy-move, mosaic, noise, removal, and sharpening. The experimental results show that the scheme achieved a PSNR value of about 51.29 dB and a SSIM value of about 0.994 on the watermarked image. The scheme showed tamper localization with accuracy of 93.8%. In addition, the proposed scheme does not require external information to perform recovery bits. The proposed scheme was able to recover the tampered image with a PSNR value of 40.45 dB and a SSIM value of 0.994