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Proceedings Paper

New approach to parallel clustering and its application to image segmentation
Author(s): Doron Hershfinkel; Its'hak Dinstein
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Paper Abstract

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.

Paper Details

Date Published: 1 November 1992
PDF: 10 pages
Proc. SPIE 1826, Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods, (1 November 1992); doi: 10.1117/12.131631
Show Author Affiliations
Doron Hershfinkel, Ben-Gurion Univ. of the Negev (Israel)
Its'hak Dinstein, Ben-Gurion Univ. of the Negev (Israel)

Published in SPIE Proceedings Vol. 1826:
Intelligent Robots and Computer Vision XI: Biological, Neural Net, and 3D Methods
David P. Casasent, Editor(s)

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