Multilevel Image Segmentation Based on an Improved Firefly Algorithm

Mathematical Problems in Engineering

Volumn 2016, Issue , 2016, Pages

  Chen, Kai ^a   Zhou, Yifan ^a   Zhang, Zhisheng ^a   Dai, Min ^a   Chao, Yuan ^a   Shi, Jinfei ^a  

^a SOUTHEAST UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BIOLUMINESCENCE; EVOLUTIONARY ALGORITHMS; FIRE PROTECTION; IMAGE SEGMENTATION; PARTICLE SWARM OPTIMIZATION (PSO);

CAUCHY MUTATION; FIREFLY ALGORITHMS; HYBRID DIFFERENTIAL EVOLUTION; LOCAL OPTIMA; MULTILEVEL IMAGE SEGMENTATIONS; OPTIMAL ALGORITHM;

OPTIMIZATION;

EID: 84959571321     PISSN: 1024123X     EISSN: 15635147     Source Type: Journal    
DOI: 10.1155/2016/1578056     Document Type: Article

References (36)

1. K. Hanbay and M. F. Talu, "Segmentation of SAR images using improved artificial bee colony algorithm and neutrosophic set," Applied Soft Computing Journal, vol. 21, pp. 433-443, 2014.
2. J. Li, X. Rao, F. Wang, W. Wu, and Y. Ying, "Automatic detection of common surface defects on oranges using combined lighting transform and image ratio methods," Postharvest Biology and Technology, vol. 82, pp. 59-69, 2013.
3. J. W. Funck, Y. Zhong, D. A. Butler, C. C. Brunner, and J. B. Forrer, "Image segmentation algorithms applied to wood defect detection," Computers and Electronics in Agriculture, vol. 41, no. 1-3, pp. 157-179, 2003.
4. N. R. Pal and S. K. Pal, "A review on image segmentation techniques," Pattern Recognition, vol. 26, no. 9, pp. 1277-1294, 1993.
5. N. Otsu, "A threshold selection method from gray-level histograms," Automatica, vol. 11, no. 285-296, pp. 23-27, 1975.
6. J. N. Kapur, P. K. Sahoo, and A. K. C. Wong, "A new method for gray-level picture thresholding using the entropy of the histogram," Computer Vision, Graphics, and Image Processing, vol. 29, no. 3, pp. 273-285, 1985.
7. J. Kittler and J. Illingworth, "Minimum error thresholding," Pattern Recognition, vol. 19, no. 1, pp. 41-47, 1986.
8. A. Abutaleb and A. Eloteifi, "Automatic thresholding of graylevel pictures using 2-D entropy," in Proceedings of the 31st Annual Technical Symposium, Applications of Digital Image Processing X, vol. 829 of Proceedings of SPIE, pp. 29-35, International Society for Optics and Photonics, San Diego, Calif, USA, January 1988.
9. K. Hammouche, M. Diaf, and P. Siarry, "A multilevel automatic thresholding method based on a genetic algorithm for a fast image segmentation," Computer Vision and Image Understanding, vol. 109, no. 2, pp. 163-175, 2008.
10. P. Ghamisi, M. S. Couceiro, J. A. Benediktsson, and N. M. F. Ferreira, "An efficientmethod for segmentation of images based on fractional calculus and natural selection," Expert Systems with Applications, vol. 39, no. 16, pp. 12407-12417, 2012.
11. Y.-C. Liang, A. H.-L. Chen, and C.-C. Chyu, "Application of a hybrid ant colony optimization for the multilevel thresholding in image processing," inNeural Information Processing, vol. 4233 of Lecture Notes in Computer Science, pp. 1183-1192, Springer, Berlin, Germany, 2006.
12. P.D. Sathya and R. Kayalvizhi, "Optimalmultilevel thresholding using bacterial foraging algorithm," Expert Systems with Applications, vol. 38, no. 12, pp. 15549-15564, 2011.
13. E. Cuevas, D. Zaldivar, and M. Pérez-Cisneros, "A novel multithreshold segmentation approach based on differential evolution optimization," Expert Systems with Applications, vol. 37, no. 7, pp. 5265-5271, 2010.
14. V. Osuna-Enciso, E. Cuevas, and H. Sossa, "A comparison of nature inspired algorithms for multi-threshold image segmentation," Expert Systemswith Applications, vol. 40, no. 4, pp. 1213-1219, 2013.
15. J. Zhang, H. Li, Z. Tang, Q. Lu, X. Zheng, and J. Zhou, "An improved quantum-inspired genetic algorithm for image multilevel thresholding segmentation," Mathematical Problems in Engineering, vol. 2014, Article ID 295402, 12 pages, 2014.
16. J.-Y. Li, Y.-D. Zhao, J.-H. Li, and X.-J. Liu, "Artificial bee colony optimizer with bee-to-bee communication and multipopulation coevolution for multilevel threshold image segmentation," Mathematical Problems in Engineering, vol. 2015, Article ID 272947, 23 pages, 2015.
17. X.-S. Yang, "Firefly algorithms formultimodal optimization," in StochasticAlgorithms: Foundations and Applications, vol. 5792of LectureNotes in Computer Science, pp. 169-178, Springer, Berlin, Germany, 2009.
18. P. Mandal, A. U. Haque, J. Meng, A.K. Srivastava, and R. Martinez, "A novel hybrid approach using wavelet, firefly algorithm, and fuzzy ARTMAP for day-ahead electricity price forecasting," IEEE Transactions on Power Systems, vol. 28, no. 2, pp. 1041-1051, 2013.
19. M. K. Sayadi, A. Hafezalkotob, and S. G. J. Naini, "Fireflyinspired algorithm for discrete optimization problems: an application to manufacturing cell formation," Journal of Manufacturing Systems, vol. 32, no. 1, pp. 78-84, 2013.
20. X.-S. Yang, S. S. Sadat Hosseini, and A. H. Gandomi, "Firefly algorithm for solving non-convex economic dispatch problems with valve loading effect," Applied Soft Computing, vol. 12, no. 3, pp. 1180-1186, 2012.
21. M.-H. Horng, "Vector quantization using the firefly algorithm for image compression," Expert Systems with Applications, vol. 39, no. 1, pp. 1078-1091, 2012.
22. Y. Zhang and L. Wu, "A novel method for rigid image registration based on firefly algorithm," International Journal of Research and Reviews in Soft and Intelligent Computing, vol. 2, no. 2, pp. 141-146, 2012.
23. T. Hassanzadeh, H. Vojodi, and F. Mahmoudi, "Non-linear grayscale image enhancement based on firefly algorithm," in Swarm, Evolutionary, and Memetic Computing, pp. 174-181, Springer, Berlin, Germany, 2011.
24. M.-H. Horng and R.-J. Liou, "Multilevel minimum cross entropy threshold selection based on the firefly algorithm," Expert Systems with Applications, vol. 38, no. 12, pp. 14805-14811, 2011.
25. T. Hassanzadeh, H. Vojodi, and A.M. E. Moghadam, "An image segmentation approach based on maximum variance intracluster method and Firefly algorithm," in Proceedings of the 7th International Conference on Natural Computation (ICNC '11), vol. 3, pp. 1817-1821, IEEE, Shanghai, China, July 2011.
26. M.-H. Horng and T.-W. Jiang, "Multilevel image thresholding selection based on the firefly algorithm," in Proceedings of the 7th International Conference on Ubiquitous Intelligence & Computing and the 7th International Conference on Autonomic & Trusted Computing (UIC/ATC '10), pp. 58-63, IEEE, Xian, China, October 2010.
27. I. Brajevic and M. Tuba, "Cuckoo search and firefly algorithm applied tomultilevel image thresholding," in Cuckoo Search and Firefly Algorithm, vol. 516 of Studies in Computational Intelligence, pp. 115-139, Springer International, New York, NY, USA, 2014.
28. S. Mohammadi, B. Mozafari, S. Solimani, and T. Niknam, "An Adaptive Modified Firefly Optimisation Algorithm based on Hong's Point Estimate Method to optimal operation management in a microgrid with consideration of uncertainties," Energy, vol. 51, pp. 339-348, 2013.
29. S.-J. Huang, X.-Z. Liu, W.-F. Su, and S.-H. Yang, "Application of hybrid firefly algorithm for sheath loss reduction of underground transmission systems," IEEE Transactions on Power Delivery, vol. 28, no. 4, pp. 2085-2092, 2013.
30. P. Shanmugavadivu and K. Balasubramanian, "Thresholded and optimized histogram equalization for contrast enhancement of images," Computers & Electrical Engineering, vol. 40, no. 3, pp. 757-768, 2014.
31. P. D. Sathya and R. Kayalvizhi, "Optimal segmentation of brain MRI based on adaptive bacterial foraging algorithm," Neurocomputing, vol. 74, no. 14-15, pp. 2299-2313, 2011.
32. H.-F. Ng, "Automatic thresholding for defect detection," Pattern Recognition Letters, vol. 27, no. 14, pp. 1644-1649, 2006.
33. X. Yao, Y. Liu, and G. Lin, "Evolutionary programming made faster," IEEE Transactions on Evolutionary Computation, vol. 3, no. 2, pp. 82-102, 1999.
34. S. Das, A. Abraham, U. K. Chakraborty, and A. Konar, "Differential evolution using a neighborhood-based mutation operator," IEEE Transactions on EvolutionaryComputation, vol. 13, no. 3, pp. 526-553, 2009.
35. H. Wang, H. Sun, C. Li, S. Rahnamayan, and J.-S. Pan, "Diversity enhanced particle swarm optimization with neighborhood search," Information Sciences, vol. 223, pp. 119-135, 2013.
36. G. Reynoso-Meza, J. Sanchis, X. Blasco, and J. M. Herrero, "Hybrid DE algorithm with adaptive crossover operator for solving real-world numerical optimization problems," in Proceedings of the IEEE Congress on Evolutionary Computation (CEC '11), pp. 1551-1556, IEEE, NewOrleans, La, USA, June 2011.