The Fuzzy C Quadric Shell clustering algorithm and the detection of second-degree curves

doi:10.1016/0167-8655(93)90103-K

Pattern Recognition Letters

Volume 14, Issue 7, July 1993, Pages 545-552

https://doi.org/10.1016/0167-8655(93)90103-K Get rights and content

Abstract

This paper introduces a new fuzzy clustering algorithm called the Fuzzy C Quadric Shells algorithm which is expressly designed to seek clusters that can be described by segments of second-degree curves, or more generally by segments of shells of hyperquadrics.

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Hence, provisions have been added to existing clustering algorithms in order to address this challenge. Repeating the clustering procedure for different numbers of clusters [32,56,57] and Progressive Clustering are two of the approaches devised in the literature. Among the many variants of Progressive Clustering are methods which start with a significantly large number of clusters and freeze “good” clusters [56,60,55,58], approaches which combine compatible clusters [20,56,60,55,58,29], and the technique of searching for one “good” cluster at a time until no more is found [48,55,88].
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The Fuzzy C Quadric Shell clustering algorithm and the detection of second-degree curves

Abstract

Pattern Recognition with Fuzzy Objective Function Algorithms

Fuzzy-shell clustering and applications to circle detection in digital images

Internat. J. General Systems

New measures for evaluating fuzzy partitions induced through C-shells clustering