A new relevance feedback technique for iconic image retrieval based on spatial relationships

被引:4
作者
Yin, Peng-Yeng [1 ]
Liu, Chin-Wen [1 ]
机构
[1] Natl Chi Nan Univ, Dept Informat Management, Nantou 54561, Taiwan
关键词
2D String; Longest common subsequence; Shortest common supersequence; Relevance feedback; SIMILARITY RETRIEVAL; KNOWLEDGE REPRESENTATION;
D O I
10.1016/j.jss.2008.09.033
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Due to the popularity of Internet and the growing demand of image access, the volume of image databases is exploding. Hence, we need a more efficient and effective image searching technology. Relevance feedback technique has been popularly used with content-based image retrieval (CBIR) to improve the precision performance, however, it has never been used with the retrieval systems based on spatial relationships. Hence, we propose a new relevance feedback framework to deal with spatial relationships represented by a specific data structure, called the 2D B-e-string. The notions of relevance estimation and query reformulation are embodied in our method to exploit the relevance knowledge. The irrelevance information is collected in an irrelevant set to rule out undesired pictures and to expedite the convergence speed of relevance feedback. Our system not only handles picture-based relevance feedback, but also deals with region-based feedback mechanism, such that the efficacy and effectiveness of our retrieval system are both satisfactory. (C) 2008 Elsevier Inc. All rights reserved.
引用
收藏
页码:685 / 696
页数:12
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