Classical Mechanics Optimization for image segmentation

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Title: Classical Mechanics Optimization for image segmentation
Authors: Khamoudj, Charaf eddineBenatchba, KarimaKechadi, Tahar
Permanent link: http://hdl.handle.net/10197/7894
Date: 14-Jun-2016
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/Report no.: Lecture Notes in Computer Science book series (LNCS, volume 10103)
Keywords: OptimisationDecision analyticsImage segmentationCombinatorial optimizationMetaheuristicClassical mechanics optimizationArtificial intelligence
DOI: 10.1007/978-3-319-50307-3_8
Other versions: http://www.mage.fst.uha.fr/icsibo2016/
Language: en
Status of Item: Peer reviewed
Is part of: 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/
Appears in Collections:Computer Science Research Collection
Insight Research Collection

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