Classical Mechanics Optimization for image segmentation

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Title: Classical Mechanics Optimization for image segmentation
Authors: Khamoudj, Charaf eddine
Benatchba, Karima
Kechadi, 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
Keywords: Optimisation;Decision analytics;Image segmentation;Combinatorial optimization;Metaheuristic;Classical mechanics optimization;Artificial intelligence
DOI: 10.1007/978-3-319-50307-3_8
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
Appears in Collections:Computer Science Research Collection
Insight Research Collection

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