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Detecting Internet visual plagiarism in higher education photography with Google™ Search by Image : proposed upload methods and system evaluation

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dc.contributor.advisor Duminy, Sylvia. I.
dc.contributor.author Van Heerden, Leanri.
dc.contributor.other Central University of Technology, Free State. Department of Design and Studio Art: Faculty of Humanities
dc.date.accessioned 2015-03-24T14:02:21Z
dc.date.available 2015-03-24T14:02:21Z
dc.date.issued 2014
dc.date.issued 2014
dc.identifier.uri http://hdl.handle.net/11462/249
dc.description Thesis (M. Tech. (Design and Studio Art)) - Central University of Technology, Free State, 2014 en_US
dc.description.abstract The Information Age has presented those in the discipline of photography with very many advantages. Digital photographers enjoy all the perquisites of convenience while still producing high-quality images. Lecturers find themselves the authorities of increasingly archaic knowledge in a perpetual race to keep up with technology. When inspiration becomes imitation and visual plagiarism occurs, lecturers may find themselves at a loss for taking action as content-based image retrieval systems, like Google™ Search by Image (SBI), have not yet been systematically tested for the detection of visual plagiarism. Currently there exists no efficacious method available to photography lecturers in higher education for detecting visual plagiarism. As such, the aim of this study is to ascertain the most effective uploading methods and precision of the Google™ SBI system which lecturers can use to establish a systematic workflow that will combat visual plagiarism in photography programmes. Images were selected from the Google™ Images database by means of random sampling and uploaded to Google™ SBI to determine if the system can match the images to their Internet source. Each of the images received a black and white conversion, a contrast adjustment and a hue shift to ascertain whether the system can also match altered images. Composite images were compiled to establish whether the system can detect images from the salient feature. Results were recorded and the precision values calculated to determine the system’s success rate and accuracy. The results were favourable and 93.25% of the adjusted images retrieved results with a precision value of 0.96. The composite images had a success rate of 80% when uploaded intact with no dissections and a perfect precision value of 1.00. Google™ SBI can successfully be used by the photography lecturer as a functional visual plagiarism detection system to match images unethically appropriated by students from the Internet. en_US
dc.format.extent 12 916 275 bytes, 1 file
dc.format.mimetype Application/PDF
dc.language.iso en_US en_US
dc.publisher Bloemfontein: Central University of Technology, Free State
dc.subject Central University of Technology, Free State - Dissertations en_US
dc.subject Photography - Copying en_US
dc.subject Plagiarism en_US
dc.subject Imitation in art en_US
dc.subject Web search engines en_US
dc.subject Dissertations, Academic - South Africa - Bloemfontein en_US
dc.title Detecting Internet visual plagiarism in higher education photography with Google™ Search by Image : proposed upload methods and system evaluation en_US
dc.type Thesis en_US
dc.rights.holder Central University of Technology, Free State

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