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dc.contributor.advisor Premaratne, SC
dc.contributor.author Maduranga, MMD
dc.date.accessioned 2017-11-27T17:28:10Z
dc.date.available 2017-11-27T17:28:10Z
dc.identifier.uri http://dl.lib.mrt.ac.lk/handle/123/12907
dc.description.abstract Using both text and image content features, a hybrid image retrieval system for Word Wide Web is developed in this paper. We first use a text-based image meta-search engine to retrieve images from the Web based on the text information on the image host pages to provide an initial image set. Because of the high-speed and low cost nature of the text-based approach, we can easily retrieve a broad coverage of images with a high recall rate and a relatively low precision. An image content based ordering is then performed on the initial image set. All the images are clustered into different folders based on the image content features. Experimental results confirm the efficiency of the system. Current image search engines on the web rely purely on the keywords around the images and the filenames, which produces a lot of garbage in the search results. Alternatively, there exist methods for content based image retrieval that require a user to submit a query image, and return images that are similar in content. We propose a novel approach named Entity resolution in sports videos using image to video, that is a hybrid of the two methods. Our algorithm first retrieves the results of a keyword query from an existing image search engine, clusters the results based on extracted image features, and returns the cluster that is inferred to be the most relevant to the search query. Furthermore, it ranks the remaining results in order of relevance en_US
dc.language.iso en en_US
dc.title Entity resolution in sports videos using image to video matching en_US
dc.type Thesis-Abstract en_US
dc.identifier.faculty IT en_US
dc.identifier.degree MSc in Information Technology. en_US
dc.identifier.department Department of Information Technology en_US
dc.date.accept 2017-05
dc.identifier.accno TH3428 en_US


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