Sketch Image Retrieval System Using Learning Method

Abstract

This paper describes an image retrieval system aimed at reducing the semantic gap by adopting relevance feedback and learning. To reduce the gap between low-level features and high-level semantics, in this image retrieval system, users'sketches play an important role in relevance feedback. Learning realizes that images are automatically relevance to the sketch images using query-by-example image retrieval. Experimental results show that this method is effective in retrieving some images.