DocumentCode
2345301
Title
Spatial Multiple Criteria Fuzzy Clustering for Image Segmentation
Author
Rajeswari, Mandava ; Wei, Bong Chin ; Yeow, Lee Song
Author_Institution
Sch. of Comput. Sci., Univ. Sains Malaysia, Minden, Malaysia
fYear
2010
fDate
28-30 Sept. 2010
Firstpage
305
Lastpage
310
Abstract
In this paper, we propose a spatial fuzzy clustering method based on multiple criteria optimization method. Our fuzzy clustering method is an enhanced version of fuzzy c-means (FCM) with consideration of multiple criteria. We initiate our multiple criteria optimization approach with two criteria in term of the features of an image: spatial information and intensity. Our spatial clustering attempts to overcome the limitation of conventional FCM. We have tested the proposed method on synthetic and coins images with added Gaussian and Salt and Pepper noises. Besides, we also experiment on real medical images (Magnetic Resonance Images (MRI)) for brain and osteosarcoma (bone tumour). The result reported was encouraging.
Keywords
feature extraction; image segmentation; optimisation; pattern clustering; Gaussian noise; Pepper noise; Salt noise; brain image; coins image; fuzzy c-means method; image segmentation; intensity feature; magnetic resonance images; multiple criteria optimization method; osteosarcoma image; spatial fuzzy clustering method; spatial information feature; Image segmentation; fuzzy clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence, Modelling and Simulation (CIMSiM), 2010 Second International Conference on
Conference_Location
Bali
Print_ISBN
978-1-4244-8652-6
Electronic_ISBN
978-0-7695-4262-1
Type
conf
DOI
10.1109/CIMSiM.2010.65
Filename
5701861
Link To Document