Title :
Generalized formulation and hypercube algorithms for relaxation labeling
Author :
Leung, Eva ; Li, Xiaobo
Author_Institution :
Dept. of Comput. Sci., Keyano Coll., Fort McMurray, Alta., Canada
fDate :
30 Apr-2 May 1991
Abstract :
Presents a generalized formulation for several well-known approaches to relaxation labeling, including discrete, fuzzy, linear probabilistic models and several nonlinear probabilistic modes. Based on this generalized framework, two parallel algorithms for SIMD hypercube computers with different numbers of processors are proposed and analyzed. The algorithms achieve minimal time complexity
Keywords :
computational complexity; parallel algorithms; relaxation theory; SIMD hypercube computers; discrete probabilistic models; fuzzy probabilistic models; hypercube algorithms; linear probabilistic models; minimal time complexity; nonlinear probabilistic modes; parallel algorithms; relaxation labeling; Algorithm design and analysis; Computer science; Computer vision; Concurrent computing; Educational institutions; Filtering; Fuzzy sets; Hypercubes; Labeling; Parallel algorithms;
Conference_Titel :
Parallel Processing Symposium, 1991. Proceedings., Fifth International
Conference_Location :
Anaheim, CA
Print_ISBN :
0-8186-9167-0
DOI :
10.1109/IPPS.1991.153758
