GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation
Abstract Image segmentation is a critical task in image processing with applications in various domains, including industry and medicine. However, multilevel thresholding, a widely used segmentation technique, suffers from high computational complexity due to the exhaustive search for optimal thresh...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-025-12142-z |
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| author | Eman Mahmoud Salem Alkhalaf Tomonobu Senjyu Masahiro Furukakoi Ashraf Hemeida Ghada Abozaid |
| author_facet | Eman Mahmoud Salem Alkhalaf Tomonobu Senjyu Masahiro Furukakoi Ashraf Hemeida Ghada Abozaid |
| author_sort | Eman Mahmoud |
| collection | DOAJ |
| description | Abstract Image segmentation is a critical task in image processing with applications in various domains, including industry and medicine. However, multilevel thresholding, a widely used segmentation technique, suffers from high computational complexity due to the exhaustive search for optimal thresholds. This paper addresses this challenge by proposing a hybrid Genetic Algorithm-Archimedes Optimization Algorithm (GAAOA), further enhanced with a Lévy flight function (GAAOA-Lévy), to improve efficiency and accuracy in multilevel thresholding. The integration of GA’s crossover mechanism strengthens local search capabilities, leading to optimal segmentation with fewer iterations. The proposed algorithm is evaluated using standard benchmark images and compared against well-known optimization techniques. Experimental results demonstrate that GAAOA-Lévy outperforms existing methods in terms of Peak Signal-to-Noise Ratio (PSNR), computational efficiency, and convergence speed, particularly excelling in three-level thresholding while reducing computational costs for higher thresholds. |
| format | Article |
| id | doaj-art-3a0393559ced4fa4888a44bfa3bac12b |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-3a0393559ced4fa4888a44bfa3bac12b2025-08-20T03:45:49ZengNature PortfolioScientific Reports2045-23222025-07-0115112410.1038/s41598-025-12142-zGAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentationEman Mahmoud0Salem Alkhalaf1Tomonobu Senjyu2Masahiro Furukakoi3Ashraf Hemeida4Ghada Abozaid5Faculty of Science, Aswan UniversityDepartment of Computer Engineering, College of Computer, Qassim UniversityDepartment of Electrical and Electronics Engineering, University of the RyukyusFaculty of EngineeringFaculty of Energy Engineering, Aswan UniversityFaculty of Engineering, Aswan UniversityAbstract Image segmentation is a critical task in image processing with applications in various domains, including industry and medicine. However, multilevel thresholding, a widely used segmentation technique, suffers from high computational complexity due to the exhaustive search for optimal thresholds. This paper addresses this challenge by proposing a hybrid Genetic Algorithm-Archimedes Optimization Algorithm (GAAOA), further enhanced with a Lévy flight function (GAAOA-Lévy), to improve efficiency and accuracy in multilevel thresholding. The integration of GA’s crossover mechanism strengthens local search capabilities, leading to optimal segmentation with fewer iterations. The proposed algorithm is evaluated using standard benchmark images and compared against well-known optimization techniques. Experimental results demonstrate that GAAOA-Lévy outperforms existing methods in terms of Peak Signal-to-Noise Ratio (PSNR), computational efficiency, and convergence speed, particularly excelling in three-level thresholding while reducing computational costs for higher thresholds.https://doi.org/10.1038/s41598-025-12142-zImage segmentationGenetic algorithm (GA)Archimedes optimization algorithm (AOA)Multilevel thresholding |
| spellingShingle | Eman Mahmoud Salem Alkhalaf Tomonobu Senjyu Masahiro Furukakoi Ashraf Hemeida Ghada Abozaid GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation Scientific Reports Image segmentation Genetic algorithm (GA) Archimedes optimization algorithm (AOA) Multilevel thresholding |
| title | GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation |
| title_full | GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation |
| title_fullStr | GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation |
| title_full_unstemmed | GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation |
| title_short | GAAOA-Lévy: a hybrid metaheuristic for optimized multilevel thresholding in image segmentation |
| title_sort | gaaoa levy a hybrid metaheuristic for optimized multilevel thresholding in image segmentation |
| topic | Image segmentation Genetic algorithm (GA) Archimedes optimization algorithm (AOA) Multilevel thresholding |
| url | https://doi.org/10.1038/s41598-025-12142-z |
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