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dc.contributor.author Tryfonos, Chrystralla en
dc.date.accessioned 2012-01-09T18:22:59Z en
dc.date.available 2012-01-09T18:22:59Z en
dc.date.issued 2010-11 en
dc.identifier.uri http://hdl.handle.net/10139/5490 en
dc.description.abstract This thesis is concerned with the development of the Refined Image Search by Example (RISE) system, which carries out web-based image searches and attempts to refine the results by utilizing an image analysis and ranking algorithm. Initially, background research is carried out regarding existing frameworks and systems for web-based image retrieval. RISE is based on the assumption that the combination of a textual and an image query can yield more meaningful search results. Specifically, the image results of a text-based search are retrieved from the web using the Google Image Search JavaScript API. Then, a combination of texture, color, and brightness low-level features is extracted from the resulting images as well as from the query image using C#. These features were selected after investigating a larger set of possible features and feature combinations using Matlab. Lastly, a similarity measure is utilized in order to determine the ranking of each resulting image with respect to the query image. Thus, the RISE image search results are presented in a refined and more relevant order using the user interface that was developed in ASP.NET and C#. en
dc.language.iso en_US en
dc.rights All rights reserved to author and California State University Channel Islands en
dc.subject RISE en
dc.subject Web searching en
dc.subject Image searching en
dc.subject Google image en
dc.title Web-Based Image Search Refinement Via Feature Extraction And Ranking en
dc.type Thesis en

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