Title
Image segmentation by multi-level thresholding based on fuzzy entropy and genetic algorithm in cloud
Abstract
In this paper, we describe a new soft computing method for segmentation of both gray level and color images by using a fuzzy entropy based criteria (cost function), the genetic algorithm, and the evolutionary computation techniques. The presented method allow us to find optimized set of parameters for a predefined cost function. Particularly, we found the optimum set of membership functions by maximizing the fuzzy entropy and based on the membership functions. Experimental results show that the offered method can reliably segment and give better threshold then Otsu Multi-Level thresholding.
Year
DOI
Venue
2015
10.1109/SYSOSE.2015.7151945
2015 10th System of Systems Engineering Conference (SoSE)
Keywords
Field
DocType
Image processing,Image segmentation,multi level thresholoding
Scale-space segmentation,Pattern recognition,Image texture,Computer science,Segmentation-based object categorization,Image segmentation,Region growing,Artificial intelligence,Thresholding,Soft computing,Genetic algorithm
Conference
Citations 
PageRank 
References 
2
0.47
6
Authors
4
Name
Order
Citations
PageRank
mohan muppidi1142.32
paul rad25711.32
Sos S. Agaian374483.01
Mo Jamshidi428952.89