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Accelerating of Image Retrieval in CBIR System with Relevance Feedback
2007
EURASIP Journal on Advances in Signal Processing
Content-based image retrieval (CBIR) system with relevance feedback, which uses the algorithm for feature-vector (FV) dimension reduction, is described. Feature-vector reduction (FVR) exploits the clustering of FV components for a given query. Clustering is based on the comparison of magnitudes of FV components of a query. Instead of all FV components describing color, line directions, and texture, only their representative members describing FV clusters are used for retrieval. In this way, the
doi:10.1155/2007/62678
fatcat:i2sbitckcjfqzimugodp2mqmbq