Parallel implementation of low-level vision operators on a hypercube machine

Mehmet Celenk; Choon Kee Lim

doi:10.1117/12.55791

1 March 1991 Parallel implementation of low-level vision operators on a hypercube machine

Mehmet Celenk, Choon Kee Lim

Author Affiliations +

Optical Engineering, Vol. 30, Issue 3, (March 1991). https://doi.org/10.1117/12.55791

Abstract

Several low-level vision algorithms have been implemented on a 16-node hypercube processor (AMETEK 5-14) by exploitation of its network embedding feature. This includes edge detection with the Sobel operator, histogramming, one-pass parallel binary image thinning, and noise cleaning. The primary objective is to parallelize these algorithms by achieving a proper image-to-processor topology mapping and to determine the actual speedup factor of parallel implementation over the sequential programming. Two basic topologies used are the ring and the nearest-neighbor networks, which are mapped onto the hypercube system. Several 512 x 512 gray-level images have been processed concurrently. A tenfold improvement in the speedup has been obtained compared to the sequential implementation in a single processor of the concurrent system. This result is obtained by ignoring the host-to-node, node-to-host, and I/O communications.

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Mehmet Celenk and Choon Kee Lim "Parallel implementation of low-level vision operators on a hypercube machine," Optical Engineering 30(3), (1 March 1991). https://doi.org/10.1117/12.55791

Published: 1 March 1991

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