Color image segmentation by multilevel thresholding based on harmony search algorithm

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Abstract

One of the important problems and active research topics in digital image precessing is image segmentation where thresholding is a simple and effective technique for this task. Multilevel thresholding is computationally complex task so different metaheuristics have been used to solve it. In this paper we propose harmony search algorithm for finding optimal threshold values in color images by Otsu’s method. We tested our proposed algorithm on six standard benchmark images and compared the results with other approach from literature. Our proposed method outperformed other approach considering all performance metrics.

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Tuba, V., Beko, M., & Tuba, M. (2017). Color image segmentation by multilevel thresholding based on harmony search algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10585 LNCS, pp. 571–579). Springer Verlag. https://doi.org/10.1007/978-3-319-68935-7_62

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