Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Comparing dissimilarity measures for content-based image retrieval
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
Overview of the ImageCLEFphoto 2008 photographic retrieval task
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
Inter-media pseudo-relevance feedback application to ImageCLEF 2006 photo retrieval
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
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This paper describes the participation of the Human Interface Laboratory of Meiji University in the ImageCLEF2008 photo retrieval task. We submitted eight retrieval runs taking two main approaches. The first approach combined Text-Based Image Retrieval (TBIR) and Context-Based Image Retrieval (CBIR). The second approach applied query expansion using conceptual fuzzy sets (CFS). A CFS is a method that uses the expression of meaning depending on the context, which an ordinary fuzzy set does not recognize. A conceptual dictionary is necessary to perform query expansion using CFS, and this is constructed by clustering. We propose here the use of query expansion with CFS and other techniques, for image retrieval that integrates different media, and we verify the utility of the system by explaining our experimental results. This time, TBIR+CFS in the system which we proposed is selected No.1 with "Text Only" runs, and we demonstrated that question expansion with CFS produced higher search results.