DocumentCode :
446110
Title :
A novel image retrieval system based on BP neural network
Author :
Han, Jun-Hua ; Huang, De-Shuang ; Lok, Tat-Ming ; Lyu, Michael R.
Author_Institution :
Inst. of Intelligent Machines, Chinese Acad. of Sci., Hefei, China
Volume :
4
fYear :
2005
fDate :
July 31 2005-Aug. 4 2005
Firstpage :
2561
Abstract :
This paper presents a novel BP-based image retrieval (BPBIR) system, which is based on the observation that the images users need are often similar to a set of images with the same conception instead of one query image and the assumption that there is a nonlinear relationship between different features. If users aren´t satisfied with the retrieved results, relevance feedback method is used to enhance the performance of the proposed system by changing the weights of the BP neural networks. In addition, we discuss some divisional methods to give rough information on the spatial color composition. Finally, we compare the performance of the proposed system with other systems. Experimental results show the efficacy of the proposed system.
Keywords :
backpropagation; image retrieval; neural nets; backpropagation neural networks; image retrieval system; relevance feedback method; spatial color composition; Computer networks; Content based retrieval; Image databases; Image retrieval; Information retrieval; Intelligent networks; Machine intelligence; Military computing; Neural networks; Neurofeedback;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
Conference_Location :
Montreal, Que.
Print_ISBN :
0-7803-9048-2
Type :
conf
DOI :
10.1109/IJCNN.2005.1556306
Filename :
1556306
Link To Document :
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