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Entropic Approach and Evolution Strategies for Optimizing the Image Segmentation by Pixel Classification: Application to Quality Control

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International Journal of Computer Applications
© 2013 by IJCA Journal
Volume 61 - Number 13
Year of Publication: 2013
Authors:
M. Merzougui
M. Nasri
B. Bouali
10.5120/9989-4834

M Merzougui, M Nasri and B Bouali. Article: Entropic Approach and Evolution Strategies for Optimizing the Image Segmentation by Pixel Classification: Application to Quality Control. International Journal of Computer Applications 61(13):22-28, January 2013. Full text available. BibTeX

@article{key:article,
	author = {M. Merzougui and M. Nasri and B. Bouali},
	title = {Article: Entropic Approach and Evolution Strategies for Optimizing the Image Segmentation by Pixel Classification: Application to Quality Control},
	journal = {International Journal of Computer Applications},
	year = {2013},
	volume = {61},
	number = {13},
	pages = {22-28},
	month = {January},
	note = {Full text available}
}

Abstract

In this paper, a segmentation method based on pixel classification and evolution strategies is proposed. Before segmentation, the number of classes is determined by the principle of maximum entropy. The proposed approach is validated on some synthetic and real images and, it shows to be very interesting as decision support in quality control.

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