Multilevel image thresholding by nature-inspired algorithms: A short review

Abstract

Nondeterministic metaheuristic optimization and digital image processing are two very different research fields, both extremely active and applicable. They touch in a very limited area, but that narrow interaction opens new very promising applications for digital image processing and new and different deployment of metaheuristic optimization. Multilevel image thresholding is very important for image segmentation, which in turn is crucial for higher level image analysis. The problem includes exponential combinatorial optimization with complex objective functions which are solvable only by nondeterministic methods. This short review presents successful applications of the nature-inspired metaheuristics to multilevel image thresholding.

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