Image Segmentation Based on World Cup Optimization Algorithm

  • Mohsen Shahrezaee Department of Mathematics, Faculty of Science, University of Imam Hussein (AS), Tehran, Iran
Keywords: Image Segmentation, Optimization, World cup optimization algorithm, Otsu, GA, APSO.

Abstract

Image segmentation has been widely used in different applications of the image processing. It The main objective of image segmentation is to subdivide the input images to their main components. Generally, the main purpose of the segmentation is to simplify or change an image representation into something that is more meaningful and easier to analyze. In this paper, World Cup Optimization Algorithm (WCO) is proposed to classify the main components of an image (pixels) into different groups. In the experiment, the proposed method performance is measured by comparing with Otsu as a classic method and GA based and APSO based image segmentation algorithms as the heuristic based algorithms for segmentation. When compared with the other segmentation methods, the proposed WCO based method achieved good performance. The final efficiency of the proposed system is compared with the described methods. Experimental results show that the proposed method has overcome the others in the performance.

References

[1] P. Ghamisi, M. S. Couceiro, J. A. Benediktsson, and N. M. Ferreira, "An efficient method for segmentation of images based on fractional calculus and natural selection," Expert Systems with Applications, vol. 39, pp. 12407-12417, 2012.
[2] N. Razmjooy, B. S. Mousavi, P. Sargolzaei, and F. Soleymani, "Image thresholding based on evolutionary algorithms," International Journal of Physical Sciences, vol. 6, pp. 7203-7211, 2011.
[3] A. Brink, "Minimum spatial entropy threshold selection," IEE Proceedings-Vision, Image and Signal Processing, vol. 142, pp. 128-132, 1995.
[4] J. N. Kapur, P. K. Sahoo, and A. K. Wong, "A new method for gray-level picture thresholding using the entropy of the histogram," Computer vision, graphics, and image processing, vol. 29, pp. 273-285, 1985.
[5] P. Moallem and N. Razmjooy, "Optimal threshold computing in automatic image thresholding using adaptive particle swarm optimization," Journal of applied research and technology, vol. 10, pp. 703-712, 2012.
[6] Y. Zhang, H. Yan, X. Zou, F. Tao, and L. Zhang, "Image Threshold Processing Based on Simulated Annealing and OTSU Method," in Proceedings of the 2015 Chinese Intelligent Systems Conference, 2016, pp. 223-231.
[7] N. Razmjooy, B. S. Mousavi, and F. Soleymani, "A hybrid neural network Imperialist Competitive Algorithm for skin color segmentation," Mathematical and Computer Modelling, vol. 57, pp. 848-856, 2013.
[8] F. Nie, P. Zhang, J. Li, and D. Ding, "A novel generalized entropy and its application in image thresholding," Signal Processing, 2016.
[9] T. Wu, R. Hou, and Y. Chen, "Cloud Model-Based Method for Infrared Image Thresholding," Mathematical Problems in Engineering, vol. 2016, 2016.
[10] O. Banimelhem and Y. A. Yahya, "Multi-thresholding image segmentation using genetic algorithm," Jordan University of Science and Technology,, Irbid, Jordan, pp. 1-6, 2011.
[11] W.-B. Tao, J.-W. Tian, and J. Liu, "Image segmentation by three-level thresholding based on maximum fuzzy entropy and genetic algorithm," Pattern Recognition Letters, vol. 24, pp. 3069-3078, 2003.
[12] N. Otsu, "A threshold selection method from gray-level histograms," Automatica, vol. 11, pp. 23-27, 1975.
[13] S. Dey, S. Bhattacharyya, and U. Maulik, "Quantum inspired genetic algorithm and particle swarm optimization using chaotic map model based interference for gray level image thresholding," Swarm and Evolutionary Computation, vol. 15, pp. 38-57, 2014.
[14] S. Kumar, P. Kumar, T. K. Sharma, and M. Pant, "Bi-level thresholding using PSO, artificial bee colony and MRLDE embedded with Otsu method," Memetic Computing, vol. 5, pp. 323-334, 2013.
[15] A. Dirami, K. Hammouche, M. Diaf, and P. Siarry, "Fast multilevel thresholding for image segmentation through a multiphase level set method," Signal Processing, vol. 93, pp. 139-153, 2013.
[16] K. C. Lin, "Fast image thresholding by finding the zero(s) of the first derivative of between-class variance," Machine Vision and Applications, vol. 13, pp. 254-262, 2003.
[17] B.-G. Kim, J.-I. Shim, and D.-J. Park, "Fast image segmentation based on multi-resolution analysis and wavelets," Pattern Recognition Letters, vol. 24, pp. 2995-3006, 12// 2003.
[18] Y. Shigemitsu, T. Ikeya, A. Yamamoto, Y. Tsuchie, M. Mishima, B. O. Smith, et al., "Evaluation of the reliability of the maximum entropy method for reconstructing 3D and 4D NOESY-type NMR spectra of proteins," Biochemical and biophysical research communications, vol. 457, pp. 200-205, 2015.
[19] N. Razmjooy, B. S. Mousavi, and F. Soleymani, "A real-time mathematical computer method for potato inspection using machine vision," Computers & Mathematics with Applications, vol. 63, pp. 268-279, 2012.
[20] N. Razmjooy, M. Khalilpour, and M. Ramezani, "A New Meta-Heuristic Optimization Algorithm Inspired by FIFA World Cup Competitions: Theory and Its Application in PID Designing for AVR System," Journal of Control, Automation and Electrical Systems, pp. 1-22, 2016.
[21] M. R. N. Razmjooy, "Model Order Reduction based on meta-heuristic optimization methods," presented at the 2016 1st International Conference on New Research Achievements in Electrical and Computer Engineering Iran, 2016.
[22] P. P. Kumar, A. Negi, B. Deekshatulu, C. Bhagvati, and A. Agarwal, "A Novel Stroke Width Based Binarization Method to Handle Closely Spaced Thick Characters," International Journal of Computer Applications, vol. 1, pp. 32-39, 2010.
[23] N. Razmjooy, A. Madadi, H.-R. Alikhani, and M. Mohseni, "Comparison of LQR and Pole Placement Design Controllers for Controlling the Inverted Pendulum," Journal of World’s Electrical Engineering and Technology, vol. 2322, p. 5114, 2014.
Published
2017-06-01
How to Cite
Shahrezaee, M. (2017). Image Segmentation Based on World Cup Optimization Algorithm. Majlesi Journal of Electrical Engineering, 11(2). Retrieved from http://mjee.iaumajlesi.ac.ir/index/index.php/ee/article/view/2213
Section
Articles