Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
387424 | Expert Systems with Applications | 2010 | 7 Pages |
Abstract
Relevance Feedback in Content-Based Image Retrieval is an active field of research. Many mechanisms of Relevance Feedback exist with many interactive techniques and implement criteria. In this paper, we proposed a novel approach of RF which can set adaptive weights of similarity measurement for each database image from the user feedback, i.e. ego-similarity measurement. We would explore the feedback records were archived in the two different ways that stored along with query images (QRF-based) or along with each retrieved relevant image from the image database (DBRF-based). In the experiment, DBRF-based relevant feedback improved greatly in the retrieval effectiveness.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Chu-Hui Lee, Meng-Feng Lin,