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.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Benzaghou, B., Barsky, D.: Nombres de Bell et somme de factorielles. Journal de Théorie des Nombres de Bordeaux 16, 1–17 (2004)
Rashedi, E., Nezamabadi, H., Saryazdi, S.: Gsa. A gravitational search algorithm. Information Sciences, 179(13): 2232–2248 (2009)
Amandeep, K., Charanjit, S., Amandeep, S.B.: SAR image segmentation based on hybrid PSOGSA optimisation algorithm, vol. 4, issue 9 (2014). ISSN 2248-9622
Barrera, J., Coello Coello, C.A.: A particle swarm optimization method for multimodal optimization based on electrostatic interaction. In: Aguirre, A.H., Borja, R.M., Garciá, C.A.R. (eds.) MICAI 2009. LNCS, vol. 5845, pp. 622–632. Springer, Heidelberg (2009)
Dahiya, A., Dubey, R.B.: Survey of some multilevel thresolding techniques for medical imaging, vol. 3 issue 7 (2015). ISSN 2347-3878
Flores, J.J., López, R., Barrera, J.: Particle swarm optimization with gravitational interactions for multimodal and unimodal problems. In: Sidorov, G., Hernández Aguirre, A., Reyes Garc\’ıa, C.A. (eds.) MICAI 2010, Part II. LNCS, vol. 6438, pp. 361–370. Springer, Heidelberg (2010)
Bichot, C.: Elaboration d’une nouvelle métaheuristique pour le partitionnement de graphe Doctoral thesis. The Polytechnic National Institute of Toulouse (2007)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
Khamoudj, C.E., Benatchba, K., Kechadi, M.T. (2016). Classical Mechanics Optimization for Image Segmentation. In: Siarry, P., Idoumghar, L., Lepagnot, J. (eds) Swarm Intelligence Based Optimization. ICSIBO 2016. Lecture Notes in Computer Science(), vol 10103. Springer, Cham. https://doi.org/10.1007/978-3-319-50307-3_8
Download citation
DOI: https://doi.org/10.1007/978-3-319-50307-3_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-50306-6
Online ISBN: 978-3-319-50307-3
eBook Packages: Computer ScienceComputer Science (R0)