Genetic Algorithm for the Extraction of Nonanalytic Objects from Multiple Dimensional Parameter Space

A new approach of the Hough transform is proposed, which makes use of the genetic searching algorithm. By using this proposed algorithm, we can resolve the main obstacle of the Hough transform, which demands an enormous amount of storage for the Hough space. The idea of this genetic Hough technique...

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Bibliographic Details
Published in:Computer vision and image understanding 1999-01, Vol.73 (1), p.1-13
Main Authors: Ser, P.K., Choy, Clifford S.T., Siu, W.C.
Format: Article
Language:English
Subjects:
Algorithmics. Computability. Computer arithmetics
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Exact sciences and technology
Pattern recognition. Digital image processing. Computational geometry
Theoretical computing
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Summary:A new approach of the Hough transform is proposed, which makes use of the genetic searching algorithm. By using this proposed algorithm, we can resolve the main obstacle of the Hough transform, which demands an enormous amount of storage for the Hough space. The idea of this genetic Hough technique is applicable to the recognition of both analytic and nonanalytic patterns. Based on the analysis of peak formation in the 4D generalized Hough transform's parameter space, a fitness function is derived, which represents the statistical weight of the existence of desired objects. By using the genetic approach to extract peaks in the parameter space, the physical storage for the 4D Hough parameter domain is not required during the detection while the accuracy of the detected parameters can be significantly improved.
ISSN:1077-3142
1090-235X
DOI:10.1006/cviu.1998.0695