Abstract
Finding the optimal threshold(s) for an image with a multimodal histogram is described in classical literature as a problem of fitting a sum of Gaussians to the histogram. The fitting problem has been shown experimentally to be a nonlinear minimization problem with local minima. In this paper, we propose to reduce the complexity of the method, by using a parameter-free particle swarm optimization algorithm, called TRIBES which avoids the initialization problem. It was proved efficient to solve nonlinear and continuous optimization problems. This algorithm is used as a “black-box” system and does not need any fitting, thus inducing time gain.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Sahoo, P.K., Soltani, S., Wong, A.K.C., Chen, Y.C.: A survey of thresholding techniques. Comput. Vis. Graphics Image Process 41, 233–260 (1988)
Nakib, A., Oulhadj, H., Siarry, P.: Image Histogram Thresholding based on multiobjective optimization. Signal Processing 87, 2516–2534 (2007)
Zahara, E., Fan, S.S., Tsai, D.: Optimal multi-thresholding using a hybrid optimization approach. Pattern Recognition Letters 26(8), 1082–1095 (2005)
Kennedy, J., Eberhart, R.C.: Particle Swarm Optimization. In: Proc. IEEE Int. Conf. On Neural Networks, WA, Australia, pp. 1942–1948 (1995)
Clerc, M.: Particle Swarm Optimization. International Scientific and Technical Encyclopaedia (2006)
Clerc, M., Kennedy, J.: The particle swarm: explosion, stability, and convergence in multi-dimensional complex space. IEEE Transactions on Evolutionary Computation 6, 58–73 (2002)
Onwubolu, G.C., Babu, B.V.: TRIBES application to the flow shop scheduling problem. In: New Optimization Techniques in Engineering, ch. 21, pp. 517–536. Springer, Heidelberg (2004)
Nawrocki, M., Dohler, M., Aghvami, A.H.: Understanding UMTS radio network modelling, Theory and Practice. Wiley, Chichester (2006)
Nakib, A., Cooren, Y., Oulhadj, H., Siarry, P.: Magnetic resonance image segmentation based on two-dimensional exponential entropy and a parameter free PSO. In: Proceedings of the 8th International Conference on Artificial Evolution, Tours, France, October 29-31 (2007)
Synder, W., Bilbro, G.: Optimal thresholding: A new approach. Pattern Recognition Letters 11, 803–810 (1990)
Romanenko, S.V., Stromberg, A.G.: Resolution of the overlapping peaks in the case of linear sweep anodic stripping voltametry via curve fitting. Chemo. and Intelligent Lab. Systems 73, 7–13 (2004)
Gonzales, R.C., Woods, R.E.: Digital image processing. Prentice Hall, Upper Sadler River (2002)
Particle Swarm Central (2006), http://www.particleswarm.info/Standard_PSO_2006
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cooren, Y., Nakib, A., Siarry, P. (2008). Image Thresholding Using TRIBES, a Parameter-Free Particle Swarm Optimization Algorithm. In: Maniezzo, V., Battiti, R., Watson, JP. (eds) Learning and Intelligent Optimization. LION 2007. Lecture Notes in Computer Science, vol 5313. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92695-5_7
Download citation
DOI: https://doi.org/10.1007/978-3-540-92695-5_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-92694-8
Online ISBN: 978-3-540-92695-5
eBook Packages: Computer ScienceComputer Science (R0)