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http://hdl.handle.net/10603/448522
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DC Field | Value | Language |
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dc.coverage.spatial | ||
dc.date.accessioned | 2023-01-18T05:37:52Z | - |
dc.date.available | 2023-01-18T05:37:52Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/448522 | - |
dc.description.abstract | newline Digital image watermarking is the most successful technique used for dealing with newlinecopyright-related issues and protection of multimedia content in today s fast-growing newlineworld. Despite of all the success of digital watermarking, it faces various problems in newlinepreservation of imperceptibility, robustness and security due to rapid development of newlineinternet and multimedia tools. To tackle these problems, various techniques have been newlinedeveloped in this proposed research work which can be utilized for ownership assertion, newlinecopy control and copyright protection of images. To show the efficacy and superiority newlineof newly developed schemes, an extensive exploration of experiments have been done newlineon the well- known standard images viz. Lena, Peppers, Baboon, Cameraman, Barbara, newlineCoins, House, and many more. newlineIn the first phase, two new optimized histogram shape-based image watermarking newlinetechniques have been proposed. As imperceptibility and robustness are contrary, a new newlineoptimized histogram shape-based watermarking scheme using genetic algorithm and newlineButterworth filtering has been proposed to hold the balance between imperceptibility newlineand robustness in the attacked environment. The extraction of low-frequency newlinecomponents from image has been performed through Butterworth filtering for holding newlineresistance against attacks. After that, the histogram shape concept has been employed newlinefor watermark embedding with the aim of maintaining perceptual quality even after newlineattacks. In continuation, the histogram range selection is taken as an optimization newlineproblem which is solved by using genetic algorithms through the fitness function. The newlinedesigned fitness function optimizes the histogram range selection in a manner that the newline© Guru Gobind Singh Indraprastha University, Dwarka, New Delhi newlinev newlineproposed watermarking process gives the best possible imperceptibility together with newlinerobustness even after attacks. The effectiveness of proposed techniques has been proved newlineby performing experiments on six different images. The exper | |
dc.format.extent | 167p. | |
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Improved Digital Image Watermarking Techniques | |
dc.title.alternative | ||
dc.creator.researcher | Sunesh | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Computer Science Artificial Intelligence | |
dc.subject.keyword | Engineering and Technology | |
dc.description.note | ||
dc.contributor.guide | R.Rama Kishore | |
dc.publisher.place | Delhi | |
dc.publisher.university | Guru Gobind Singh Indraprastha University | |
dc.publisher.institution | University School of Information and Communication Technology | |
dc.date.registered | 2014 | |
dc.date.completed | 2020 | |
dc.date.awarded | 2022 | |
dc.format.dimensions | 29.5 | |
dc.format.accompanyingmaterial | CD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | University School of Information and Communication Technology |
Files in This Item:
File | Description | Size | Format | |
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80_recommendation.pdf | Attached File | 142.2 kB | Adobe PDF | View/Open |
sunesh thesis (2).pdf | 2.43 MB | Adobe PDF | View/Open |
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