Accelerating of Image Retrieval in CBIR System with Relevance Feedback

Autor: Branimir Reljin, Irini Reljin, Nikola Reljin, Stevan Rudinac, Maja Rudinac, Vladan Radosavljević, Goran Zajić, Nenad Kojić
Jazyk: angličtina
Rok vydání: 2007
Předmět:
Zdroj: EURASIP Journal on Advances in Signal Processing, Vol 2007 (2007)
Druh dokumentu: article
ISSN: 1687-6172
1687-6180
DOI: 10.1155/2007/62678
Popis: 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 “curse of dimensionality” is bypassed since redundant components of a query FV are rejected. It was shown that about one tenth of total FV components (i.e., the reduction of 90%) is sufficient for retrieval, without significant degradation of accuracy. Consequently, the retrieving process is accelerated. Moreover, even better balancing between color and line/texture features is obtained. The efficiency of FVR CBIR system was tested over TRECVid 2006 and Corel 60 K datasets.
Databáze: Directory of Open Access Journals
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