Pein, Raoul Pascal and Lu, Joan (2010) Multi-feature query language for image classification. Procedia Computer Science, 1 (1). pp. 2533-2541. ISSN 1877-0509
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Abstract
Despite the major effort put into the creation of Content-Based Image Retrieval (CBIR) system
during the last decade, the solutions available are still not satisfying for generic purposes.
The most severe issue seems to be the so-called “semantic gap”. It is feasible to define and use
domain specific feature vectors on a low level and use this information for a similarity based retrieval.
Yet, mapping these to higher level semantics remains dicult. This research investigates
a domain-independent way of automatized image categorization. A CBIR query language is constructed
to build query-like descriptors for each category to be learned. The proposed learning
algorithm is based on decision-trees. The resulting descriptors are aimed to be understandable
and modifiable by expert users. A case-study is presented to support these claims.
| Item Type: | Article |
|---|---|
| Additional Information: | Paper presented at the International Conference on Computational Science (iccs) 2010 University of Amsterdam The Netherlands May 31 - June 2, 2010 |
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
| Schools: | School of Computing and Engineering School of Computing and Engineering > Diagnostic Engineering Research Centre School of Computing and Engineering > Diagnostic Engineering Research Centre > Measurement System and Signal Processing Research Group School of Computing and Engineering > Informatics Research Group School of Computing and Engineering > Informatics Research Group > Software Engineering Research Group School of Computing and Engineering > Informatics Research Group > XML, Database and Information Retrieval Research Group |
| Related URLs: | |
| Depositing User: | Raoul Pein |
| Date Deposited: | 25 May 2010 11:38 |
| Last Modified: | 09 Dec 2010 12:32 |
| URI: | http://eprints.hud.ac.uk/id/eprint/7671 |
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