New approach to parallel clustering and its application to image segmentation
Doron Hershfinkel, Its'Hak Dinstein · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1992
The proposed parallel clustering technique performs several clustering processes (for the same data set) in parallel, using different sets of initial cluster centers. Each clustering process consists of a sequence of iterations. The clustering processes are iterated in parallel within each parallel step. By the end of each parallel step, the clustering parameters are evaluated according to prespecified criteria. 'Non-promising' cluster center sets are discarded, and new cluster center sets are formed using 'promising' cluster centers. The presented illustrated examples indicate a reduction of 7% to 30% in the number of iterations required for convergence.