ADVANCED RELEVANCE FEEDBACK STRATEGY FOR PRECISE IMAGE RETRIEVAL

ABSTRACT Relevance feedback is effective technique for bridging the semantic gap in image retrieval which diminish semantic gap between low-level visual features and high-level semantic concepts for image retrieval. Currently, crucial image retrieval system is content-based image retrieval. To improve performance of proposed content based image retrieval system, automatic relevance feedback technique is proposed which based on inductive learning involve inductive concept learning by decision tree. We implement and tested proposed image retrieval system which refine the retrieval result as per user requirement until get required accuracy. Experimental result shows improved performance in term of precision, recall and accuracy