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A generic fuzzy rule based technique for image segmentation

Karmakar, G. C. and Dooley, L. S. (2001). A generic fuzzy rule based technique for image segmentation. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '01), 7-11 May 2001, Salt Lake City, Utah.

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Many fuzzy clustering based techniques do not incorporate the spatial relationships of the pixels, while all fuzzy rule based image segmentation techniques tend to be very much application dependent. In most techniques, the structure of the membership functions are predefined and their parameters are either automatically or manually determined. This paper addresses the aforementioned problems by introducing a general fuzzy rule based image segmentation technique, which is application independent and can also incorporate the spatial relationships of the pixels. It also proposes the automatic defining of the structure of the membership functions. A qualitative comparison is made between the segmentation results using this method and the popular fuzzy c-means (FCM) applied to two types of images: light intensity (LI) and an X-ray of the human vocal tract. The results clearly show that this method exhibits significant improvements over FCM for both types of images

Item Type: Conference Item
Extra Information: ISBN: 0-7803-7041-4
Academic Unit/Department: Mathematics, Computing and Technology > Computing & Communications
Mathematics, Computing and Technology
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 11664
Depositing User: Laurence Dooley
Date Deposited: 12 Sep 2008 01:11
Last Modified: 25 Feb 2016 14:13
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