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Reducing Semantic Gap in Content-Based Image Retrieval Systems Using Graph Cuts and Fuzzy Relevance Feedback
,
M.Sc. Thesis
Sharif University of Technology
;
Tabandeh, Mahmoud
(Supervisor)
Abstract
Multimedia retrieval systems are gradually playing a critical role in our everyday life to facilitate interacting with massive amount of personal or professional images, music and video archives. So far, many systems have been proposed among them relevance feedback based content based multimedia (especially image) retrievals has been proved to be more effective. However there is still a problem called semantic gap, in finding proper mapping between low-level features used by CBIR systems and user’s high-level concepts. On the other hand graph cuts have been a great powerful tool for solving many computer vision problems. They benefit from robust optimization algorithm called maximum flow/...