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Classical Mechanics Optimization for image segmentation

Author(s)
Khamoudj, Charaf eddine  
Benatchba, Karima  
Kechadi, Tahar  
Uri
http://hdl.handle.net/10197/7894
Date Issued
2016-06-14
Embargo end date
2018-06-14
Abstract
In this work, we focus on image segmentation by simulating the natural phenomenon of the bodies moving through space. For this, a subset of image pixels is regularly selected as planets and the rest as satellites. The attraction force is defined by Newton’s third law (gravitational interaction) according to the distance and color similarity. In the first phase of the algorithm, we seek an equilibrium state of the earth-moon system in order to achieve the second phase, in which we search an equilibrium state of the earth-apple system. As a result of these two phases, bodies in space are constructed; they represent segments in the image. The objective of this simulation is to find and then extract the multiple segments from an image.
Type of Material
Conference Publication
Series
Lecture Notes in Computer Science book series (LNCS, volume 10103)
Subjects

Optimisation

Decision analytics

Image segmentation

Combinatorial optimiz...

Metaheuristic

Classical mechanics o...

Artificial intelligen...

DOI
10.1007/978-3-319-50307-3_8
Web versions
http://www.mage.fst.uha.fr/icsibo2016/
Language
English
Status of Item
Peer reviewed
Journal
ICSIBO 2016: Swarm Intelligence Based Optimization
Conference Details
International Conference on Swarm Intelligence Based Optimization: Theoretical Advances and Real World Application (ICSIBO’2016), UHA, Mulhouse, France, 13-14 June 2016
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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insight_publication.pdf

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643.11 KB

Format

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Checksum (MD5)

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Owning collection
Insight Research Collection
Mapped collections
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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