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图像检索中相关反馈技术的特性研究 被引量:2

Characteristic Research of Relevance Feedback Technology in Image Retrieval
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摘要 介绍了基于内容的图像检索技术以及一些图像检索系统存在的局限性,分析了为解决此局限而引入的相关反馈技术的机制,它将人也作为检索系统的一个部分,根据用户的反馈重新查询,从而提高检索精度。 并将相关反馈技术分成3类,研究了采用相关反馈技术的图像检索系统的时序特性。 The paper introduces the technique of content-based image retrieval (CBIR) and the limitation of many developed retrieval system, attaches much importance to the mechanism of relevance feedback(RF), which is introduced to break the limitation. The RF looks on the customers as a part of retrieval system and retrieves again according to the feedback information of customers to improve the accuracy of retrieval. And it analyzes three kinds of RF and elaborates on the time sequence characteristic of image retrieval system with RF.
出处 《计算机工程》 CAS CSCD 北大核心 2004年第7期128-129,169,共3页 Computer Engineering
关键词 基于内容的图像检索 相关反馈 相似性 时序特性 Content-based image retrieval(CBIR) Relevance feedback(RF) Similarity Time sequence characteristic
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  • 1[1]Rui Y,Huang T S,Ortega M,et al.Relevance feedback: A power tool in int eractive content-based image retrieval [J].IEEE Trans on Circuits and Syst fo r Video Tech,1998,8(5): 644-655.
  • 2[2]Rui Y,Huang T S.A novel relevance feedback technique in image retrieval [A].Proc 7th ACM Int Conf on Multimedia (part 2) [C].Orlando,Florida,199 9.67-70.
  • 3[3]Ishikawa Y,Subramanya R,Faloutsos C.Mindreader: Query Databases Through Multiple Examples [A].Proc 24th Int Conf on Very Large Databases [C].New York,1998.218-227.
  • 4[4]Vapnik V.The Nature of Statistical Learning Theory [M].New York: Sprin ger Verlag,1995.
  • 5[5]Burges C J C.A tutorial on support vector machines for pattern recognitio n [J].Data Mining and Knowledge Discovery,1998,2(2): 1-47.
  • 6[6]Osuna E.Applying SVMs to face detection [J].IEEE Intelligent Systems,1998,13(4): 23-26.
  • 7[7]Chapelle O,Haffner P,Vapnik V.Support vector machines for histogram-bas ed image classification [J].IEEE Trans on neural networks,1999,10(5): 1057 -1064.
  • 8[8]Huang J,Kumar S R,Mitra M,et al.Image indexing using color correlogram s [A].Proc.of IEEE conf.on Computer Vision and Pattern Recognition [C].S an Juan,Puerto Rico,1997.762-768.
  • 9Rui Y,Proc ACM Multimedia'99,1999年,67页
  • 10Lee C,SPIE Symposium on Voice Video and Data Communications Multimedia Storage and Archiving Systems IV,1999年,20页

共引文献50

同被引文献19

  • 1雷方元,郝重阳,王海南,郑建铧,樊养余.一种基于颜色块直方图的图像检索方法[J].计算机应用研究,2004,21(5):173-174. 被引量:5
  • 2张恒博,欧宗瑛.一种基于色彩和灰度直方图的图像检索方法[J].计算机工程,2004,30(10):20-22. 被引量:40
  • 3[2]DANEELS DIRK,VAN CAMPENHOUT DAVID,NIBLACA WAYNE,et al.Interactive Outlining:An Improved Approach Using Active Contours[J].Proceedings of the International Society of Optical Engineering,Proc SPIE Storage and Retrieval for Image and Video Databases(1908),1993:226-233.
  • 4[3]RW PICARD,T PMINKA.Vision Texture for Annotation Multimedia Systems[J].ACM /Springer Verlag Journal of Multimedia Systems,1995(3):3-14.
  • 5[4]W Y MA,B S MANJUNATH.Image Indexing Using a Texture Dictionary[J].Digital Image Storage Archiving Systems 2606,1995:288-298.
  • 6[5]W Y MA,B S MANJUNATH.Texture Features and Learning Similarity[J].USA:Proceedings of IEEE International Conference on Computer Vision and Pattern Recognition,1996:425-430.
  • 7[6]JOHN R SMITH,SHIH FU CHANG.An Image and Video Search Engine for the World Wide Web[J].Proc.SPIE Storage and Retrieval for Image and Video Databases,1997:84-95.
  • 8[11]BUCKLEY C,SALTON G.Optimization of Relevance Feedback Weights[M].Washington:Proc.of SIGIR,1995:351-35.
  • 9[12]MITCHELL T.Machine Learning[M].New York:McCraw Hill,1997:98-10.
  • 10[13]LI Mingjing,CHEN Zheng,ZHANG Hong-jiang.Statistical Correlation Analysis in Image Retrieval[J].Pattern Recognition,2002,35(12):2687-2693.

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