Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
MindReader: Querying Databases Through Multiple Examples
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Color-spatial image indexing and applications
Color-spatial image indexing and applications
Feature re-weighting in content-based image retrieval
CIVR'06 Proceedings of the 5th international conference on Image and Video Retrieval
Relevance feedback: a power tool for interactive content-based image retrieval
IEEE Transactions on Circuits and Systems for Video Technology
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Relevance Feedback is a useful technique to reduce semantic gap which is a bottleneck to a successful Content-Based Image Retrieval system. In this paper, we have discussed an Instance-based relevance feedback method that uses the closeness or similarity of an instance to a class of similar instances. We have achieved improvement in retrieval accuracy by incorporating cluster density of relevant images in addition to the nearness of an image from the relevant and non-relevant image sets. We have experimented with four databases with total image numbers ranging from 1000 to 19511, encompassing both narrow domain and broad domain. With the cluster density approach, we have achieved an improvement of up to 3.7% in averaged precision value as compared to an existing method.