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- A Novel Hybrid Gray Wolf Optimization Algorithm with Harmony Search to Solve Multi-Level Image Thres...
A Novel Hybrid Gray Wolf Optimization Algorithm with Harmony Search to Solve Multi-Level Image Thresholding Problem
Authors : Alper Ünlü, Ilhan Ilhan
Pages : 230-245
Doi:10.47112/neufmbd.2023.21
View : 48 | Download : 60
Publication Date : 2023-12-31
Article Type : Research
Abstract :Multi-level image thresholding is an important image processing technique used to separate an image into advanced meaningful features. By using this technique together with metaheuristic optimization algorithms, successful results can be achieved in terms of computational time. In this study, a hybrid algorithm called GWO-HS was proposed to solve the multi-level image thresholding problem. The proposed algorithm was obtained by hybridizing the Gray Wolf Optimization (GWO) and Harmony Search (HS) algorithms. The performance of the GWO-HS algorithm was compared with the performances of five other algorithms. Otsu and Kapur entropy-based thresholding methods were used in the comparisons. In the experiments, six images, which are well known and widely used in image processing studies, were preferred. Thresholding was applied for threshold levels ranging from 2 to 10 on each image. The results showed that the proposed GWO-HS algorithm has superior performance compared to other algorithms, especially for high threshold levels.Keywords : Gri Kurt Optimizasyon, Harmoni arama, Kapur, Çok seviyeli görüntü eşikleme, Otsu.