SELF–ORGANIZING MAP COMBINED WITH A FUZZY CLUSTERING FOR COLOR IMAGE SEGMENTATION OF EDIBLE BEANS

2003 ◽  
Vol 46 (3) ◽  
Author(s):  
Y. Chtioui ◽  
S. Panigrahi ◽  
L. F. Backer
2021 ◽  
pp. 227-238
Author(s):  
P. Ganesan ◽  
B. S. Sathish ◽  
L. M. I. Leo Joseph ◽  
B. Girirajan ◽  
P. Anuradha ◽  
...  

Author(s):  
Sourav De ◽  
Siddhartha Bhattacharyya ◽  
Susanta Chakraborty

A self-supervised image segmentation method by a non-dominated sorting genetic algorithm-II (NSGA-II) based optimized MUSIG (OptiMUSIG) activation function with a multilayer self-organizing neural network (MLSONN) architecture is proposed to segment multilevel gray scale images. In the same way, another NSGA-II based parallel version of the OptiMUSIG (ParaOptiMUSIG) activation function with a parallel self-organizing neural network (PSONN) architecture is purported to segment the color images in this article. These methods are intended to overcome the drawback of their single objective based counterparts. Three standard objective functions are employed as the multiple objective criteria of the NSGA-II algorithm to measure the quality of the segmented images.


2019 ◽  
Vol 23 (1) ◽  
Author(s):  
J. M. Barrón Adame ◽  
M. S. Acosta Navarrete ◽  
J. Quintanilla Domínguez ◽  
R. Guzmán Cabrera ◽  
M. Cano Contreras ◽  
...  

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