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Parallel vision techniques on the hypercube computer

Bond, Alan H. and Fashena, David (1988) Parallel vision techniques on the hypercube computer. In: C3P Proceedings of the third conference on Hypercube concurrent computers and applications. Vol.2. ACM , New York, NY, pp. 1007-1010. ISBN 0-89791-278-0. http://resolver.caltech.edu/CaltechAUTHORS:20160810-110257182

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Abstract

Parallel algorithms for programming low-level vision mechanisms on the JPL-Caltech hypercube are reported. These concern principally edge and region finding. 256x256 8bit images were used. We discuss the problem of programming a hypercube computer, and the Caltech approach to load balancing. We then discuss the distribution of images over the hypercube and the I/O problem for images. In edge finding, we programmed convolution using a separable kernel computational approach. This was tested with 5x5 and 32x32 masks. In region finding, we developed two different parallel histogram techniques. The first finds a global histogram for the image by a completely parallel technique. This method, which was developed from the Fox-Furmanski scalar product method, allows each histogram bucket to be computed by a separate processor, each processor regarding the hypercube as a different tree, and all buckets being computed in parallel by a complete interleaving of all communications required. Similarly the global histogram can then be distributed over the hypercube, so that all processors have the entire global histogram, by an completely parallel technique. The second histogramming method finds a spatially local histogram within each processor and then connects locally found regions together. Work in progress includes the application of a Hopfield neural net approach to region finding.


Item Type:Book Section
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http://dx.doi.org/10.1145/63047.63054DOIArticle
http://dl.acm.org/citation.cfm?doid=63047.63054PublisherArticle
Additional Information:© 1988 ACM. We should like to acknowledge the suggestion of Geoffrey Fox to apply the scalar product method to the histogram problem. We are grateful to Professor David Jefferson of UCLA for his encouragement. This work was supported through the Caltech Concurrent Computation Program, by a grant from the US Department of Energy.
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Funding AgencyGrant Number
Caltech Concurrent Computation ProgramUNSPECIFIED
Department of Energy (DOE)UNSPECIFIED
Record Number:CaltechAUTHORS:20160810-110257182
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20160810-110257182
Official Citation:A. H. Bond and D. Fashena. 1989. Parallel vision techniques on the hypercube computer. In Proceedings of the third conference on Hypercube concurrent computers and applications - Volume 2 (C3P), Geoffrey Fox (Ed.), Vol. 2. ACM, New York, NY, USA, 1007-1010. DOI=http://dx.doi.org/10.1145/63047.63054
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:69538
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:10 Aug 2016 18:11
Last Modified:10 Aug 2016 18:11

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