DocumentCode :
2702782
Title :
An Improved Fuzzy Clustering Method to Detect Moving Objects
Author :
Lu, Yu ; Zhu, Hao ; Wu, Qinzhang
Author_Institution :
Chinese Acad. of Sci., Chengdu
fYear :
2007
fDate :
15-19 Dec. 2007
Firstpage :
15
Lastpage :
18
Abstract :
The classical fuzzy clustering method needs to determine the number of group for classification before all samples are processed and the number of group is fixed during iteration, which dose not help to ensure the classification precision. Considering this, an improved fuzzy clustering method with elastic grouping logic is proposed. The elastic grouping logic, based on the samples´ ascriptions and their distances to the centers of each group, can dynamically adjust the number of group and achieve the accurate classification. Our improved clustering method is applied in the optical flow field. The experimental results show that our method has superiority over the classical clustering method in precision and can detect the moving object with precision.
Keywords :
fuzzy set theory; image classification; object detection; pattern clustering; classification precision; elastic grouping logic; fuzzy clustering; moving objects detection; Automobiles; Clustering methods; Computational intelligence; Fuzzy logic; Image motion analysis; Motion detection; Object detection; Pattern recognition; Pixel; Security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Security Workshops, 2007. CISW 2007. International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-0-7695-3073-4
Type :
conf
DOI :
10.1109/CISW.2007.4425435
Filename :
4425435
Link To Document :
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