다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기
Information retrieval journal, v.3 no.3, 2000년, pp.229 - 241
Csillaghy, A. (Space Sciences Laboratory, University of California, Berkeley CA 94720-7450. csillag@ssl.berkeley.edu) , Hinterberger, H. (Institute of Scientific Computing, ETH-Zentrum, CH-8092 Zurich, Switzerland. hinterberger@inf.ethz.ch) , Benz, A.O. (Institute of Astronomy, ETH-Zentrum, CH-8092 Zurich, Switzerland. benz@astro.phys.ethz.ch)
Content-based image retrieval in astronomy needs methods that can deal with an image content made of noisy and diffuse structures. This motivates investigations on how information should be summarized and indexed for this specific kind of images. The method we present first summarizes the image information content by partitioning the image in regions with same texture. We call this process texture summarization. Second, indexing features are generated by examining the distribution of parameters describing image regions. Indexing features can be associated with global or local image characteristics. Both kinds of indexing features are evaluated on the retrieval system of the Zurich archive of solar radio spectrograms. The evaluation shows that generating local indexing features using self-organizing maps yields the best effectiveness of all tested methods.
해당 논문의 주제분야에서 활용도가 높은 상위 5개 콘텐츠를 보여줍니다.
더보기 버튼을 클릭하시면 더 많은 관련자료를 살펴볼 수 있습니다.
Copyright KISTI. All Rights Reserved.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.