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| Content Provider | Springer Nature Link |
|---|---|
| Author | Ajorloo, Hossein Lakdashti, Abolfazl |
| Copyright Year | 2012 |
| Abstract | In this paper, we propose a mapping from low level feature space to the semantic space drawn by the users through relevance feedback to enhance the performance of current content based image retrieval (CBIR) systems. The proposed approach makes a rule base for its inference and configures it using the feedbacks gathered from users during the life cycle of the system. Each rule makes a hypercube (HC) in the feature space corresponding to a semantic concept in the semantic space. Both short and long term strategies are taken to improve the accuracy of the system in response to each feedback of the user and gradually bridge the semantic gap. A scoring paradigm is designed to determine the effective rules and suppress the inefficient ones. For improving the response time, an HC merging approach and, for reducing the conflicts, an HC splitting method is designed. Our experiments on a set of 11 000 images from the Corel database show that the proposed approach can better describe the semantic content of images for image retrieval with respect to some existing approaches reported recently in the literature. Moreover, our approach can be better trained and is not saturated in long time, i.e., any feedback improves the precision and recall of the system. Another strength of our method is its ability to address the dynamic nature of the image database such that it can follow the changes occurred instantaneously and permanently by adding and dropping images. |
| Starting Page | 147 |
| Ending Page | 162 |
| Page Count | 16 |
| File Format | |
| ISSN | 10009000 |
| Journal | Journal of Computer Science and Technology |
| Volume Number | 27 |
| Issue Number | 1 |
| e-ISSN | 18604749 |
| Language | English |
| Publisher | Springer US |
| Publisher Date | 2012-01-09 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | image retrieval relevance feedback rule base hypercube (HC) Theory of Computation Artificial Intelligence (incl. Robotics) Computer Science Information Systems Applications (incl. Internet) Data Structures, Cryptology and Information Theory Software Engineering |
| Content Type | Text |
| Resource Type | Article |
| Subject | Theoretical Computer Science Computational Theory and Mathematics Computer Science Applications Software Hardware and Architecture |
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