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