scholarly journals Multilevel Thresholding Color Image Segmentation Using a Modified Artificial Bee Colony Algorithm

2018 ◽  
Vol E101.D (8) ◽  
pp. 2064-2071 ◽  
Author(s):  
Sipeng ZHANG ◽  
Wei JIANG ◽  
Shin'ichi SATOH
2014 ◽  
Vol 687-691 ◽  
pp. 3652-3655
Author(s):  
Yong Hao Xiao ◽  
Zhuo Bin He ◽  
Yao Hu ◽  
Wei Yu Yu

Segmentation of noisy images is one of the most challenging problems in image analysis. It hasn’t yet been solved very well. In this paper, we propose a new method for image segmentation, which is able to segment two kinds of noisy images. The experimental results prove that Artificial Bee Colony Algorithm performs better for two types of noisy images.


2011 ◽  
Vol 214 ◽  
pp. 693-698
Author(s):  
Rui Geng

The colony intellectual behavior performed by many organisms in nature can solve various kinds of problems on scientific and technological research. Bees are a socialized insect colony, which perform different types of activities according to their different divisions of labor, and achieve information sharing and exchanges among the bee colony to find the optimal solution for problems. According to this characteristic, researchers have proposed the algorithm of bee colony for solving combinatorial optimization problems. In this paper, it will describe the implementation process of such an image segmentation algorithm, and the result shows that this method is a potential image segmentation algorithm.


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