Fuzzy C-Means Image Segmentation Algorithm Based on Chaotic Simulated Annealing

2014 ◽  
Vol 624 ◽  
pp. 536-539 ◽  
Author(s):  
Qing Yang ◽  
Zhi Qiang Wang ◽  
Yan Xu
Keyword(s):  
Image Segmentation ◽  
Simulated Annealing ◽  
Optimal Solution ◽  
Optimization Method ◽  
Segmentation Algorithm ◽  
Global Optimization Method ◽  
Fuzzy C Means ◽  
Global Optimal ◽  
Chaotic Simulated Annealing ◽  
Image Segmentation Algorithm

Considering the problem that the traditional fuzzy c-means (FCM) image segmentation algorithm is often caught in a specific range in local search and fails to get the globally optimal solution, this paper proposed a modified FCM algorithm based on chaotic simulated annealing (CSA). It traverse all the states without repetition within a certain range to calculate the optimal solution. Experimental results show that our method converges more quickly and accurately to the global optimal and proves a promise global optimization method of high adaptability and feasibility.

CSFCM: An improved fuzzy C-Means image segmentation algorithm using a cooperative approach

2021 ◽  
Vol 166 ◽  
pp. 114063
Author(s):  
Hamza Abdellahoum ◽  
Nassim Mokhtari ◽  
Abderrahmane Brahimi ◽  
Abdelmadjid Boukra
Keyword(s):  
Image Segmentation ◽  
Segmentation Algorithm ◽  
Fuzzy C Means ◽  
Cooperative Approach ◽  
Image Segmentation Algorithm

Color Image Segmentation Based on Self-Organizing Maps

2011 ◽  
Vol 214 ◽  
pp. 693-698
Author(s):  
Rui Geng
Keyword(s):  
Image Segmentation ◽  
Optimization Problems ◽  
Color Image ◽  
Optimal Solution ◽  
Implementation Process ◽  
Segmentation Algorithm ◽  
Color Image Segmentation ◽  
Combinatorial Optimization Problems ◽  
Bee Colony ◽  
Image Segmentation Algorithm

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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