Digital image registration using structured genetic algorithm


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.

Publication Title

Proceedings of SPIE - The International Society for Optical Engineering

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