2012 | OriginalPaper | Chapter
Approach to Image Segmentation Based on Interval Type-2 Fuzzy Subtractive Clustering
Authors : Long Thanh Ngo, Binh Huy Pham
Published in: Intelligent Information and Database Systems
Publisher: Springer Berlin Heidelberg
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The paper deals with an approach to image segmentation using interval type-2 fuzzy subtractive clustering (IT2-SC). The IT2-SC algorithm is proposed based on extension of subtractive clustering algorithm (SC) with fuzziness parameter
m
. And to manage uncertainty of the parameter
m
, we have expanded the SC algorithm to interval type-2 fuzzy subtractive clustering (IT2-SC) using two fuzziness parameters
m
1
and
m
2
which creates a footprint of uncertainty (FOU) for the fuzzifier. The input image is extracted RGB values as input space of IT2-SC; number of clusters is automatically identified based on parameters of the algorithm and image properties. The experiments of image segmentation are implemented in variety of images with statistics.