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Proceedings Paper

Digital image registration using structured genetic algorithm
Author(s): Dipankar Dasgupta; Douglas R. McGregor
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Paper Abstract

This paper describes a new genetic approach called the structured genetic algorithm (sGA) for automatic registration of digital images. The specialty of this genetic model lies primarily in its redundant genetic material and a gene activation mechanism which utilizes a multi-layered structure for the chromosome. The additional genetic material serves to retain multiple optional solution spaces in parameter optimization. The structured genetic model is applied here to minimize the registration measures in image transformations, as investigated by Fitzpatrick and Grefenstatte with the simple GA. The results demonstrate that sGA is a much faster and robust search method that is guaranteed to reach a global optimum by adaptively estimating the subspace from the maximum space during the evolutionary process. Preliminary experimental results are reported.

Paper Details

Date Published: 16 December 1992
PDF: 9 pages
Proc. SPIE 1766, Neural and Stochastic Methods in Image and Signal Processing, (16 December 1992); doi: 10.1117/12.130831
Show Author Affiliations
Dipankar Dasgupta, Univ. of Strathclyde (United States)
Douglas R. McGregor, Univ. of Strathclyde (United Kingdom)

Published in SPIE Proceedings Vol. 1766:
Neural and Stochastic Methods in Image and Signal Processing
Su-Shing Chen, Editor(s)

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