Paper Info
Title
A generic fuzzy rule based technique for image segmentation
Abstract
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.
Year
DOI
Venue
2001
10.1109/ICASSP.2001.941235
ICASSP
Keywords
Field
DocType
image segmentation technique,automatic defining,fuzzy clustering,aforementioned problem,generic fuzzy rule,general fuzzy rule,membership function,popular fuzzy c-means,segmentation result,spatial relationship,fuzzy rule,human voice,vocal tract,knowledge based systems,pixel,polynomials,clustering algorithms,pixels,spatial relationships,image segmentation,geometry,shape,information technology,fuzzy logic
Fuzzy clustering,Scale-space segmentation,Pattern recognition,Defuzzification,Fuzzy classification,Computer science,Fuzzy logic,Segmentation-based object categorization,Image segmentation,Artificial intelligence,Fuzzy rule
Conference
ISBN
Citations 
PageRank 
0-7803-7041-4
5
0.62
References 
Authors
3
2
Name
Order
Citations
PageRank
G. C. Karmakar1182.19
L. Dooley2121.15