Time-weighted quantitative testing of image segmentation with a genetic algorithm

Automatic parameter selection for image segmentation is accelerated by means of a genetic algorithm (GA). Issues remain in selecting the population size, number of generations, and termination of the search. As evaluation time and subsequent image batch-processing time, when the algorithm is applied in practice, are important considerations, this paper introduces a time factor into the GA cost function. It is found that this procedure while preserving the GA solution also improves interpretation and parameter selection.