대한전자공학회:학술대회논문집 (Proceedings of the IEEK Conference)
- 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
- /
- Pages.669-672
- /
- 2001
관련성 피드백을 이용한 효과적인 내용기반 영상검색
Effective Content-Based Image Retrieval Using Relevance feedback
초록
We propose an efficient algorithm for an interactive content-based image retrieval using relevance feedback. In the proposed algorithm, a new query feature vector first is yielded from the average feature vector of the relevant images that is fed back from the result images of the previous retrieval. Each component weight of a feature vector is computed from an inverse of standard deviation for each component of the relevant images. The updated feature vector of the query and the component weights are used in the iterative retrieval process. In addition, the irrelevant images are excluded from object images in the next iteration to obtain additional performance improvement. In order to evaluate the retrieval performance of the proposed method, we experiment for three image databases, that is, Corel, Vistex, and Ultra databases. We have chosen wavelet moments, BDIP and BVLC, and MFS as features representing the visual content of an image. The experimental results show that the proposed method yields large precision improvement.
키워드