DocumentCode
1879001
Title
Research of the Image Segmentation Based on Ant Colony Algorithm
Author
Yan, Zhe ; Gu, Han-Ming
Author_Institution
Inst. of Geophys. & Geomatics, China Univ. of Geosci., Wuhan, China
fYear
2009
fDate
27-29 May 2009
Firstpage
106
Lastpage
109
Abstract
Ant colony algorithm, based on behavior of real ants, is a natural approach to establish from their nest to food source. An ant moves randomly and detects a previously laid pheromone on a path in order to find the shortest way between their nest and the food source. Ant system algorithm is an important methodology to apply on non-linear optimal problems recently. Each ant chooses the next position to visit in accordance with the visibility of the position and the pheromone intensity. In this paper, an ant colony algorithm for image segmentation is proposed. We discuss the ideas behind ant algorithms and describe how they have been implemented with regards to the image segmentation problem. The proposed approach has been tested on different images. The experimental results demonstrate the effectiveness and practicability of the proposed algorithm.
Keywords
image segmentation; optimisation; ant colony algorithm; image segmentation; Artificial intelligence; Cities and towns; Distributed computing; Geophysics; Image analysis; Image segmentation; Insects; Intelligent networks; Software algorithms; Software engineering; ant colony; image segmentation; iterations;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering, Artificial Intelligences, Networking and Parallel/Distributed Computing, 2009. SNPD '09. 10th ACIS International Conference on
Conference_Location
Daegu
Print_ISBN
978-0-7695-3642-2
Type
conf
DOI
10.1109/SNPD.2009.58
Filename
5286684
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