Image Authenticity and Perceptual Optimization via Genetic Algorithm and a Dependence Neighborhood

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@Article{usman:2007:IJAMCS,

• author = "Imran Usman and Asifullah Khan and Rafiullah Chamlawi and Abdul Majid",
• title = "Image Authenticity and Perceptual Optimization via Genetic Algorithm and a Dependence Neighborhood",
• journal = "International Journal of Applied Mathematics and Computer Sciences",
• year = "2007",
• volume = "4",
• number = "1",
• pages = "615--620",
• keywords = "genetic algorithms, genetic programming, Digital watermarking, fragile watermarking, Image authentication",
• ISSN = "1305-5313",
• URL = "http://www.waset.org/ijamcs/v4/v4-1-7.pdf",
• size = "6 pages",
• abstract = "Information hiding for authenticating and verifying the content integrity of the multimedia has been exploited extensively in the last decade. We propose the idea of using genetic algorithm and non-deterministic dependence by involving the unwatermarkable coefficients for digital image authentication. Genetic algorithm is used to intelligently select coefficients for watermarking in a DCT based image authentication scheme, which implicitly watermark all the un-watermarkable coefficients also, in order to thwart different attacks. Experimental results show that such intelligent selection results in improvement of imperceptibility of the watermarked image, and implicit watermarking of all the coefficients improves security against attacks such as cover-up, vector quantisation and transplantation.",
• notes = "Broken Dec 2022 http://www.waset.org/ijamcs/",

}

Genetic Programming entries for Imran Usman Asifullah Khan Rafiullah Chamlawi Abdul Majid

Citations