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New Technology of Library and Information Service  2007, Vol. 2 Issue (10): 42-46    DOI: 10.11925/infotech.1003-3513.2007.10.10
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Study on Feedback Noise and Suppression Algorithm in Image Semantic Retrieval
Wang Nan   Zhao Pengwei   Dou Yongxiang   Qin Chunxiu   Zhao Fei
 (School of Economy and Management, Xidian University, Xi’an 710071,China)
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Feedback noise in image semantic retrieval is a key issue in this paper. Firstly, the bad effect of feedback noise on the semantic network method is analysed. After that, an algorithm of relevance feedback based on voting idea is proposed, which is robust to feedback noise. Then an analysis is made on the performance of the proposed algorithm. Finally, further study issues are pointed out.

Key wordsImage semantic retrieval      Relevance feedback      Feedback noise      Voting idea      Semantic matrix     
Received: 20 August 2007      Published: 25 October 2007


Corresponding Authors: Wang Nan     E-mail:
About author:: Wang Nan,Zhao Pengwei,Dou Yongxiang,Qin Chunxiu,Zhao Fei

Cite this article:

Wang Nan,Zhao Pengwei,Dou Yongxiang,Qin Chunxiu,Zhao Fei. Study on Feedback Noise and Suppression Algorithm in Image Semantic Retrieval. New Technology of Library and Information Service, 2007, 2(10): 42-46.

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[1] 王崇骏,杨育彬,陈世福. 基于高层语义的图像检索算法[J]. 软件学报,2004,15(10):1461-1462.
[2] Colombo C, Bimbo A D, Pala P. Semantics in Visual Information Retrieval[J]. IEEE Multimedia,1999,6(3):38-53.
[3] Yong Rui, Thomas S.Huang,Ortega M, et al. Relevance Feedback:A Power Tool for Interactive Content-based Image Retrieval[J]. IEEE CSVT,1998,8(5):644-655.
[4] 吴洪,卢汉青,马颂得. 基于内容图像检索中相关反馈技术的回顾[J]. 计算机学报,2005,28(12):1969-1979.
[5] 朱兴全,张洪江,刘文印,等. iFind:一个结合语义和视觉特征的图像相关反馈检索系统[J]. 计算机学报,2002,25(7):681-687.
[6] Jincheng Huang, Yao Wang. Compression of Color Facial Images Using Feature Correction Two-Stage Vector Quantization[J]. IEEE Trans on Image Processing,1999,8(1):102-108.
[7] Samal A, Iyengar P A. Automatic Recognition and Analysis for Human Faces and Facial Expressions: A Survey[J]. Pattern Recognition,1992,25(1):65-77.
[8] Lee S Y, Ham Y K, Park R H. Recognition of Human Front Faces Using KnoWledge-based Feature Extraction and Neuro-fuzzy Algorithm[J]. Pattern Recognition,1996,29(11):1863-1876.
[9] Xiaofei He, Oliver King, Weiying Ma,et al. Learning a Semantic Space from User’s Relevance Feedback for Image Retrieval[J].IEEE Transactions on Circuits and Systems for Video Technology,2003,13(1):39-40.
[10] 沈玉利,郭雷,耿苑. 一种新型图像检索语义网络构建方法[J]. 计算机应用研究,2005,22(10):148.
[11] 陈勇跃,张玉峰. 基于机器学习的图像检索机制的研究[J]. 情报理论与实践,2004,27(5):534.
[12] Changbo Yang, Ming Dong, Farshad Fotouhi. Semantic Feedback for Interactive Image Retrieval[J].ACM,2005(2):415.

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