A Relevance Feedback Image Retrieval Scheme Using Multi-Instance and Pseudo Image Concepts

淡江大學機構典藏 > 全球發展學院 > 資訊創新與科技學系 > 期刊論文 > Item 987654321/64008

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題名:	A Relevance Feedback Image Retrieval Scheme Using Multi-Instance and Pseudo Image Concepts
作者:	Chang, F. C.;Hang, H.-M.
貢獻者:	淡江大學資訊軟體學系
日期:	2006-05-01
上傳時間:	2011-10-20 11:15:55 (UTC+8)
摘要:	Content-based image search has long been considered a difficult task. Making correct conjectures on the user intention (perception) based on the query images is a critical step in the content-based search. One key concept in this paper is how we find the user preferred image characteristics from the multiple positive samples provided by the user. The second key concept is that when the user does not provide a sufficient number of samples, how we generate a set of consistent "pseudo images". The notion of image feature stability is thus introduced. The third key concept is how we use negative images as pruning criterion. In realizing the preceding concepts, an image search scheme is developed using the weighted low-level image features. At the end, quantitative simulation results are used to show the effectiveness of these concepts.
關聯:	IEICE Trans. on Information and Systems E89-D(5), pp.1720-1731
DOI:	10.1117/12.586678
顯示於類別:	[資訊創新與科技學系] 期刊論文

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