Mapping adaptive fuzzy Kohonen clustering network onto distributed image processing system

Authors:
Mikhail S. Tarkov;Youngsong Mun;Jaeyoung Choi;Hyung-Il Choi
Affiliations:
Fault-tolerant Computer Systems Department, Institute of Semiconductor Physics, Siberian Branch, Russian Academy of Sciences, 13, Lavrentieva avenue, 630090 Novosibirsk, Russia;School of Computing, Soongsil University, 1-1 Sang-do 5 dong, Dong Jak-gu, Seoul, South Korea;School of Computing, Soongsil University, 1-1 Sang-do 5 dong, Dong Jak-gu, Seoul, South Korea;School of Computing, Soongsil University, 1-1 Sang-do 5 dong, Dong Jak-gu, Seoul, South Korea
Venue:
Parallel Computing
Year:
2002

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Abstract

Algorithm of mapping adaptive fuzzy Kohonen clustering network (AFKCN) onto an image processing system with distributed memory and torus topology is presented. A hypercube is used as a structure of the AFKCN parallel program for image segmentation. The impossibility of message congestions on torus links is proved for the hypercube-to-torus XOR-embedding. Expressions for the parallel AFKCN performance analysis are given. For distributed image processing systems having two- and three-measured torus topologies the analysis shows good estimation of the parallel AFKCN implementation.