Title :
Image segmentation using modified extended fuzzy rules
Author :
Karmakar, Gour C. ; Dooley, Laurence S. ; Murshed, Manzur
Author_Institution :
Gippsland Sch. of Comput. & Inf. Technol., Monash Univ., Churchill, Vic., Australia
Abstract :
The extended fuzzy rules for image segmentation (EFRIS) algorithm initially splits all segmented regions into mutually exclusive 4-connected objects, from which the largest one in each region is designated as its main object. A drawback of this approach is that it is less effective when the main objects are relatively small and some of the other objects are completely surrounded and connected to the main object of another region. Besides possessing insufficient merging rules, EFRIS also only considers the surrounding main objects in the original order that the regions were segmented, which is undesirable. A new general segmentation algorithm called modified extended fuzzy rules for image segmentation (MEFRIS) is presented, which addresses these problems and whose improved segmentation performance is analysed and numerically evaluated. The results are also contrasted with both the original generic fuzzy rule-based image segmentation (GFRIS) and EFRIS algorithms.
Keywords :
fuzzy logic; image segmentation; knowledge based systems; digital image processing; image segmentation; main object; modified extended fuzzy rules; Algorithm design and analysis; Australia; Clustering algorithms; Digital images; Image segmentation; Merging; Sprites (computer); Testing; Tires;
Conference_Titel :
Signal Processing, 2002 6th International Conference on
Print_ISBN :
0-7803-7488-6
DOI :
10.1109/ICOSP.2002.1179942