Technical Program

Paper Detail

Paper:	IMDSP-L5.3
Session:	Image Segmentation
Time:	Wednesday, May 17, 14:40 - 15:00
Presentation:	Lecture
Topic:	Image and Multidimensional Signal Processing: Image Segmentation
Title:	OBJECT BASED IMAGE SEGMENTATION USING FUZZY CLUSTERING
Authors:	Mohammad Ameer Ali, Laurence S. Dooley, Gour C. Karmakar, Monash University, Australia
Abstract:	Existing shape-based clustering algorithms, including fuzzy k-rings, fuzzy k-elliptical, circular c-shell, and fuzzy c-shell ellipsoidal are all designed to segment regular geometrically shaped objects such as circles, ellipses or combination of both. These algorithms however, are unsuitable for segmenting arbitrary-shaped objects, so in an attempt to address this issue, a fuzzy image segmentation of generic shaped clusters (FISG) algorithm was introduced that integrated generic shape information into the segmentation framework. It however, had a number of limitations relating to the mathematical derivation of the updated contour radius, the initial shape representation, and the impact of overlapping clusters. This paper proposes a new object based segmentation using fuzzy clustering (OSF) algorithm that solves these drawbacks by controlling the scaling of original shape, securing a better initial shape representation and avoids cluster overlapping, with both qualitative and quantitative results confirming the improved overall segmentation performance.