Template based fuzzy c-shells clustering algorithm and its fast implementation

The fuzzy c-shells (FCS) clustering algorithms are widely applied in pattern recognition and computer vision. However, the available FCS algorithms are valid only for detecting the hyper-spherical-shell or hyper-ellipsoidal-shell type clusters, which limits their applications. In this paper, a template based fuzzy c-shells (TBFCS) clustering algorithm is proposed. Its fast implementation is also given. This approach can obtain better clustering performance for any-shell type clusters, so that it is used more widely than the existing FCS algorithms. The effectiveness of the proposed algorithm is illustrated with experimental results.