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2017 | OriginalPaper | Chapter

Color Image Segmentation by Multilevel Thresholding Based on Harmony Search Algorithm

Authors : Viktor Tuba, Marko Beko, Milan Tuba

Published in: Intelligent Data Engineering and Automated Learning – IDEAL 2017

Publisher: Springer International Publishing

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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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Metadata
Title
Color Image Segmentation by Multilevel Thresholding Based on Harmony Search Algorithm
Authors
Viktor Tuba
Marko Beko
Milan Tuba
Copyright Year
2017
Book
Intelligent Data Engineering and Automated Learning – IDEAL 2017

Print ISBN: 978-3-319-68934-0

Electronic ISBN: 978-3-319-68935-7

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-68935-7_62

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