DocumentCode :
2009694
Title :
Image similarity matching retrieval on synergetic neural network
Author :
Li, Hui ; Ma, Xiuli ; Wan, Wanggen ; Zhou, Xueli
Author_Institution :
Sch. of Commun. & Inf. Eng., Shanghai Univ., Shanghai, China
fYear :
2010
fDate :
23-25 Nov. 2010
Firstpage :
1566
Lastpage :
1571
Abstract :
In this paper, an image similarity matching retrieval algorithm based on synergetic neural network (SNN) is proposed. It is a novel method with advantages of no pseudo-state and closer to natural self-organization process in the field of image retrieval. It utilizes feature vector extraction, attention parameter selection, order parameter calculation, pseudo-inverse matrix and its determinant value comparison to achieve better retrieval effect. Due to the structural characteristic of synergetic neural network, it can save time for iteration and improve efficiency and speed. The experimental results show that this algorithm has fast speediness, strong robustness and high accuracy, and provides greater generality and high real-time performance.
Keywords :
feature extraction; image matching; image retrieval; matrix algebra; neural nets; attention parameter selection; determinant value comparison; feature vector extraction; image similarity matching retrieval; natural self-organization process; order parameter calculation; pseudo inverse matrix; synergetic neural network; Accuracy; Artificial neural networks; Euclidean distance; Image retrieval; Pattern recognition; Prototypes; Vectors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Audio Language and Image Processing (ICALIP), 2010 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-5856-1
Type :
conf
DOI :
10.1109/ICALIP.2010.5684499
Filename :
5684499
Link To Document :
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