Otsu's criterion-based multilevel thresholding by a nature-inspired metaheuristic called Galaxy-based Search Algorithm

In this paper, image segmentation of gray-level images is performed by multilevel thresholding. The optimal thresholds for this purpose are found by maximizing the between-class variance (the Otsu's criterion). The optimization is conducted by a newly-developed nature-inspired metaheuristic cal...

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Bibliographic Details
Main Author: Shah-Hosseini, H.
Format: Conference Proceeding
Language:English
Subjects:
Biology
chaos
Image segmentation
Logistics
metaheuristic
Optimization
Otsu
Silicon
Space exploration
Spirals
thresholding
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Summary:In this paper, image segmentation of gray-level images is performed by multilevel thresholding. The optimal thresholds for this purpose are found by maximizing the between-class variance (the Otsu's criterion). The optimization is conducted by a newly-developed nature-inspired metaheuristic called "Galaxy-based Search Algorithm" or the GbSA. The proposed GbSA resembles the spiral arms of some galaxies to search for the optimal thresholds. The GbSA also uses a modified Hill Climbing algorithm as a local search. The experimental results show that the GbSA finds the optimal or very near optimal thresholds in all runs of the algorithm.
DOI:10.1109/NaBIC.2011.6089621