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Performance Evaluation of ACO based Metaheuristic Technique for Color Image Segmentation

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
Authors:
Baljot Kaur, P. S. Mann
10.5120/ijca2017913043

Baljot Kaur and P S Mann. Performance Evaluation of ACO based Metaheuristic Technique for Color Image Segmentation. International Journal of Computer Applications 160(4):31-35, February 2017. BibTeX

@article{10.5120/ijca2017913043,
	author = {Baljot Kaur and P. S. Mann},
	title = {Performance Evaluation of ACO based Metaheuristic Technique for Color Image Segmentation},
	journal = {International Journal of Computer Applications},
	issue_date = {February 2017},
	volume = {160},
	number = {4},
	month = {Feb},
	year = {2017},
	issn = {0975-8887},
	pages = {31-35},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume160/number4/27063-2017913043},
	doi = {10.5120/ijca2017913043},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

The aim of image segmentation is to make simpler presentation of an image into incredible which is meaningful as well as easy to understand. It is mainly utilized to know the location of objects, boundaries, lines etc in the digital images. Clustering technique is a method which shows the data set or pixels are replaced by cluster, pixels might be together because of the same color, texture etc. This paper represents the implementation of an ACO based metaheuristic for color image segmentation to differentiate the mixed regions.

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Keywords

Image Processing, Image Segmentation Techniques, FELICM, Ant Colony Optimization.