Experimental evaluation of hypercube-based range analysis tools

Author

Perez, P. ; Abidi, M.A. ; Gonzalez, R.C.

Author_Institution

Dept. of Electr. & Comput. Eng., Tennessee Univ., Knoxville, TN, USA

Volume

fYear

1990

fDate

16-21 Jun 1990

Firstpage

584

Abstract

Parallel range segmentation tools are analyzed in terms of a general model for distributed-memory algorithms using n-cube topologies. The model explicitly relates the concepts of speedup, efficiency and load balancing and provides criteria for optimum assignment of nodes. Low-level computer vision functions are classified as either local or global. Experimental results are given showing that the efficiency of local operators is determined by load balancing, while the efficiency of global operators is more dependent on communication overhead

Keywords

computerised pattern recognition; computerised picture processing; hypercube networks; parallel processing; distributed-memory algorithms; hypercube-based range analysis tools; low-level computer vision functions; parallel range segmentation tools; Algorithm design and analysis; Computer vision; Condition monitoring; Geometry; Image segmentation; Layout; Load management; Parallel algorithms; Pixel; Real time systems;

fLanguage

English

Publisher

ieee

Conference_Titel

Pattern Recognition, 1990. Proceedings., 10th International Conference on

Conference_Location

Atlantic City, NJ

Print_ISBN

0-8186-2062-5

Type

conf

DOI

10.1109/ICPR.1990.119435

Filename

119435

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3388910