Image retrieval with feature selection and relevance feedback

This paper proposes a new content based image retrieval (CBIR) system combined with relevance feedback and the online feature selection procedures. A measure of inconsistency from relevance feedback is explicitly used as a new semantic criterion to guide the feature selection. By integrating the user feedback information, the feature selection is able to bridge the gap between low-level visual features and high-level semantic information, leading to the improved image retrieval accuracy. Experimental results show that the proposed method obtains higher retrieval accuracy than a commonly used approach.

• Type: Journal
• Year: 2010
• Where: ICIP
• Authors: Yu Sun, Bir Bhanu
• Keywords: Feature Selection, ICIP 2010, Image Processing, Relevance Feedback, Retrieval Accuracy