A comparison of clustering algorithms applied to color image quantization
Pattern Recognition Letters - special issue on pattern recognition in practice V
Clustering with a genetically optimized approach
IEEE Transactions on Evolutionary Computation
A weighted sum validity function for clustering with a hybrid niching genetic algorithm
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A comparison of fuzzy shell-clustering methods for the detection of ellipses
IEEE Transactions on Fuzzy Systems
Fuzzy shell clustering algorithms in image processing: fuzzy C-rectangular and 2-rectangular shells
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Possibilistic shell clustering of template-based shapes
IEEE Transactions on Fuzzy Systems
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We present in this paper a new type of alternating-optimization based possibilistic c-shell clustering algorithm called possibilistic c-template (PCT). A template is represented by a set of line segments. A cluster prototype consists of a copy of the template after translation, scaling, and rotation transforms. This extends the capability of shell clustering beyond a few standard geometrical shapes that have been studied so far. We use a number of 2-dimensional data sets to illustrate the application of our algorithm in detecting generic template-based shapes in images. Techniques taken to relax the requirements of known number of clusters and good initialization are also described. Results for both synthetic and actual image data are presented.