Hypercube algorithms suitable for image understanding in uncertain environments

Author

Huntsberger, T.L. ; Sengupta, A.

Author_Institution

Dept. of Comput. Sci., Univ. of South Carolina, Columbia, SC, USA

fYear

1988

fDate

10-12 Oct 1988

Firstpage

101

Lastpage

103

Abstract

Parallel algorithms for color image segmentation and edge detection are presented and analyzed. These algorithms are part of a recently developed computer vision system which uses multiple-valued logic to represent uncertainty in the imaging process and in intermediate results. Algorithms for the extraction of three-dimensional properties of objects using dynamic scene analysis techniques within the same computer vision system framework are briefly examined. Results from experimental studies using a 1024-element hypercube implementation of the algorithms as applied to a series of natural scenes are reported

Keywords

computer vision; computerised pattern recognition; many-valued logics; parallel algorithms; 1024-element hypercube implementation; color image segmentation; computer vision; dynamic scene analysis; edge detection; hypercube algorithms; image understanding; multiple-valued logic; parallel algorithms; uncertain environments; Algorithm design and analysis; Computer vision; Hypercubes; Image analysis; Image color analysis; Image edge detection; Image segmentation; Logic; Parallel algorithms; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Frontiers of Massively Parallel Computation, 1988. Proceedings., 2nd Symposium on the Frontiers of

Conference_Location

Fairfax, VA

Print_ISBN

0-8186-5892-4

Type

conf

DOI

10.1109/FMPC.1988.47419

Filename

47419