Titlebook: Metaheuristic Algorithms for Image Segmentation: Theory and Applications; Diego Oliva,Mohamed Abd Elaziz,Salvador Hinojosa Book 2019 Sprin

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FLORA

FLAGR

,Image Segmentation Using Kapur’s Entropy and a Hybrid Optimization Algorithm,ch six images are used as test and the results are compared with four different algorithms. The Experimental results provides an evident about the high performance of the proposed SSAABC method in terms of the performance measures such as PSNR, SSIM, and CPU time(s).

HAUNT

Image Segmentation with Minimum Cross Entropy,the MCET directly impacts the performance of the method. Current approaches take a large number of iterations to converge and a high rate of MCET function evaluations. This chapter presents the use of evolutionary algorithms for multilevel thresholding using the MCET.

打算

Image Segmentation as a Multiobjective Optimization Problem,evaluate the segmented images and Hypervolume to assess the solutions. The experimental results show that the proposed method outperforms the other multiobjective algorithms based on the performance measures.

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古老

Humble

Multilevel Thresholding for Image Segmentation Based on Metaheuristic Algorithms,ation algorithm. The objective function, performance measures, and the number of images and thresholds that applied on the studies are mentioned. The review concludes that the multilevel thresholding segmentation is a challenge and many studies till now work to solve it.

armistice

Tsallis Entropy for Image Thresholding,roblems as they usually require many evaluations before delivering an acceptable result. This chapter introduces the use of evolutionary algorithms to improve segmentation process using the Tsallis entropy for search the best thresholds.