Approach to image segmentation based on interval type-2 fuzzy subtractive clustering

Authors:
Long Thanh Ngo;Binh Huy Pham
Affiliations:
Department of Information Systems, Faculty of Information Technology, Le Quy Don Technical University, Hanoi, Vietnam;Department of Information Systems, Faculty of Information Technology, Le Quy Don Technical University, Hanoi, Vietnam
Venue:
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part II
Year:
2012

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Abstract

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 m1 and m2 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.