Title :
Geometric primitive extraction using a genetic algorithm
Author :
Roth, Gerhard ; Levine, Martin D.
Author_Institution :
Inst. for Inf. Technol., Nat. Res. Council of Canada, Ottawa, Ont., Canada
Abstract :
A genetic algorithm based on a minimal subset representation of a geometric primitive is used to perform primitive extraction. A genetic algorithm is an optimization method that uses the metaphor of evolution, and a minimal subset is the smallest number of points necessary to define a unique instance of a geometric primitive. The approach is capable of extracting more complex primitives than the Hough transform. While similar to a hierarchical merging algorithm, it does not suffer from the problem of premature commitment
Keywords :
genetic algorithms; pattern recognition; genetic algorithm; geometric primitive extraction; hierarchical merging algorithm; minimal subset representation; optimization; Biological cells; Computer vision; Cost function; Councils; Data mining; Equations; Genetic algorithms; Information technology; Optimization methods; Solid modeling;
Conference_Titel :
Computer Vision and Pattern Recognition, 1992. Proceedings CVPR '92., 1992 IEEE Computer Society Conference on
Conference_Location :
Champaign, IL
Print_ISBN :
0-8186-2855-3
DOI :
10.1109/CVPR.1992.223120
