Parallel Algorithms for Computer Vision on the Connection Machine

dc.creator	Little, James J.
dc.date	2004-10-01T20:10:31Z
dc.date	2004-10-01T20:10:31Z
dc.date	1986-11-01
dc.date.accessioned	2013-10-09T02:40:14Z
dc.date.available	2013-10-09T02:40:14Z
dc.date.issued	2013-10-09
dc.identifier	AIM-928
dc.identifier	http://hdl.handle.net/1721.1/5597
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721
dc.description	The Connection Machine is a fine-grained parallel computer having up to 64K processors. It supports both local communication among the processors, which are situated in a two-dimensional mesh, and high-bandwidth communication among processors at arbitrary locations, using a message-passing network. We present solutions to a set of Image Understanding problems for the Connection Machine. These problems were proposed by DARPA to evaluate architectures for Image Understanding systems, and are intended to comprise a representative sample of fundamental procedures to be used in Image Understanding. The solutions on the Connection Machine embody general methods for filtering images, determining connectivity among image elements, determining spatial relations of image elements, and computing graph properties, such as matchings and shortest paths.
dc.format	31 p.
dc.format	4037682 bytes
dc.format	1518931 bytes
dc.format	application/postscript
dc.format	application/pdf
dc.language	en_US
dc.relation	AIM-928
dc.title	Parallel Algorithms for Computer Vision on the Connection Machine

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