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

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          Abstract

          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 used it to benchmark a number of digital watermarking algorithms involving two types of watermarks for content authentication and self-restoration purposes. The benchmarking results demonstrated the advantages of the proposed benchmarking framework, and also gave us some useful insights about existing image authentication and self-restoration watermarking algorithms which are an important but less studied topic in digital watermarking.

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          Most cited references23

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          Secure spread spectrum watermarking for multimedia.

          This paper presents a secure (tamper-resistant) algorithm for watermarking images, and a methodology for digital watermarking that may be generalized to audio, video, and multimedia data. We advocate that a watermark should be constructed as an independent and identically distributed (i.i.d.) Gaussian random vector that is imperceptibly inserted in a spread-spectrum-like fashion into the perceptually most significant spectral components of the data. We argue that insertion of a watermark under this regime makes the watermark robust to signal processing operations (such as lossy compression, filtering, digital-analog and analog-digital conversion, requantization, etc.), and common geometric transformations (such as cropping, scaling, translation, and rotation) provided that the original image is available and that it can be successfully registered against the transformed watermarked image. In these cases, the watermark detector unambiguously identifies the owner. Further, the use of Gaussian noise, ensures strong resilience to multiple-document, or collusional, attacks. Experimental results are provided to support these claims, along with an exposition of pending open problems.
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            Rotation, scale, and translation resilient watermarking for images

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              Watermarking schemes evaluation

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                Author and article information

                Journal
                2015-05-31
                2015-06-05
                Article
                1506.00243
                5322308c-b367-49af-8d93-f66ef2ae5462

                http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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                Custom metadata
                cs.MM cs.CR cs.PF

                Performance, Systems & Control,Security & Cryptology,Graphics & Multimedia design

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