Abstract: In the case that sample is out of database, retrieval precision of the existing image retrieval methods based on linear manifold learning has smaller increase after feedback. Aiming at this problem, this paper proposes an image retrieval method based on Relevance Feedback(RF) and manifold reconstruction. It reconstructs sample into structure graph which needs to be reserved by computing the nearest neighbor in relevance feedback, thus can meet the need of that the distance between similar images and sample is mapped as near as possible. Experimental result shows that the method can improve retrieval precision while merely increase milliseconds time.
Content-based Image Retrieval(CBIR),
manifold structure reconstruction,