Multilevel Image Thresholding Memanfaatkan Firefly Algorithm, Improved Bat Algorithm, dan Symbiotic Organisms Search
نویسندگان
چکیده
منابع مشابه
Improved Bat Algorithm Applied to Multilevel Image Thresholding
Multilevel image thresholding is a very important image processing technique that is used as a basis for image segmentation and further higher level processing. However, the required computational time for exhaustive search grows exponentially with the number of desired thresholds. Swarm intelligence metaheuristics are well known as successful and efficient optimization methods for intractable ...
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The drawback of the conventional multilevel thresholding methods is high computational cost since they do exhaustive search among exponentialy growing number of possible thresholds to optimize the objective functions. In this paper a new multilevel thresholding method based on cuckoo search (CS) algorithm is proposed in order to overcome this obstacle. The optimal thresholds are found by maximi...
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Thresholding is an important approach for image segmentation and it is the first step in the image processing for many applications. Segmentation is a low level operation that can segment an image in nonoverlapping regions. The optimal thresholds are found by maximizing Kapur's entropy-based thresholding function in a grey level image. However, the required CPU time increases exponentially with...
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Symbiotic organisms search (SOS) is a new robust and powerful metaheuristic algorithm, which stimulates the symbiotic interaction strategies adopted by organisms to survive and propagate in the ecosystem. In the supervised learning area, it is a challenging task to present a satisfactory and efficient training algorithm for feedforward neural networks (FNNs). In this paper, SOS is employed as a...
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ژورنال
عنوان ژورنال: Journal of Intelligent System and Computation
سال: 2019
ISSN: 2722-1962,2621-9220
DOI: 10.52985/insyst.v1i1.24