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Opto-Electronics Review

Editor-in-Chief: Jaroszewicz, Leszek

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1896-3757
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Volume 16, Issue 2

Issues

Finite grade pheromone ant colony optimization for image segmentation

F. Yuanjing / Y. Li / K. Liangjun
Published Online: 2008-03-26 | DOI: https://doi.org/10.2478/s11772-008-0009-0

Abstract

By combining the decision process of ant colony optimization (ACO) with the multistage decision process of image segmentation based on active contour model (ACM), an algorithm called finite grade ACO (FACO) for image segmentation is proposed. This algorithm classifies pheromone into finite grades and updating of the pheromone is achieved by changing the grades and the updated quantity of pheromone is independent from the objective function. The algorithm that provides a new approach to obtain precise contour is proved to converge to the global optimal solutions linearly by means of finite Markov chains. The segmentation experiments with ultrasound heart image show the effectiveness of the algorithm. Comparing the results for segmentation of left ventricle images shows that the ACO for image segmentation is more effective than the GA approach and the new pheromone updating strategy appears good time performance in optimization process.

Keywords: active contour model; ant colony optimization; image segmentation

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About the article

Published Online: 2008-03-26

Published in Print: 2008-06-01


Citation Information: Opto-Electronics Review, Volume 16, Issue 2, Pages 163–171, ISSN (Online) 1896-3757, DOI: https://doi.org/10.2478/s11772-008-0009-0.

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© 2008 SEP, Warsaw. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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