Metaheuristic Optimization Design for Image Segmentation: Applications to Brain MRI Images

Metaheuristic Optimization Design for Image Segmentation: Applications to Brain MRI Images

  IJCTT-book-cover
 		 International Journal of Computer Trends and Technology (IJCTT)          
 
© 2017 by IJCTT Journal
Volume-54 Number-1
Year of Publication : 2017
Authors : Sara Riahi, Azzeddine Riahi
DOI :  10.14445/22312803/IJCTT-V54P109

MLA

Sara Riahi, Azzeddine Riahi "Metaheuristic Optimization Design for Image Segmentation: Applications to Brain MRI Images". International Journal of Computer Trends and Technology (IJCTT) V54(1):40-55, December 2017. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
This paper presents a new approach for image segmentation based on the metaheuristic "Optimization by Ant Colonies". It is a method of classification without initial partition required or information a priori. It is based on the principle of stochastic exploration of a combined ant colony with the theory of Markov fields for modeling the field labels, and field observations. We propose to use the metaheuristic ant colonies to estimate the fields of labels and build an optimal partition of the image.

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Keywords
Segmentation, Classification, Optimization, Ant Colony, Pareto, Metaheuristics.