Mineral Belt Image Segmentation Using Firefly Algorithm

Li Fang He; Xiong Tong; Song Wei Huang

doi:10.4028/www.scientific.net/AMR.989-994.4074

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 989-994Mineral Belt Image Segmentation Using Firefly...

Mineral Belt Image Segmentation Using Firefly Algorithm

Abstract:

Otsu is one of better image segmentation algorithm, which obtains optimum threshold by maximizing the between-class variance of an image. However, computation time will sharply increase as the threshold increase. In order to greatly improve the problem, a new segmentation algorithm called firefly algorithm based on Otsu’s method is presented in this paper, and applied the algorithm to segmentation of mineral belt image of shaking table, which lay the foundation for automation of shaking table. Experimental results show that the new algorithm can accurately segment different mineral belts and can obtain the same optimal thresholds and fitness values with Otsu’s method.

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Periodical:

Advanced Materials Research (Volumes 989-994)

Pages:

4074-4077

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.989-994.4074

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Online since:

July 2014

Authors:

Li Fang He*, Xiong Tong, Song Wei Huang

Keywords:

Firefly Optimization (FA), Image Segmentation, Mineral Belt Image, Otsu

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* - Corresponding Author

References

[1] Dengyuan Huang, Chiahung Wang: Pattern Recognition Letters. 30(2009)275-284.

Google Scholar

[2] Nobuyuki Otsu: IEEE Trans. Sys., Man., Cyber. 9 (1979)62–66.

Google Scholar

[3] Pingsung Liao , Tse-sheng Chen , Pau-Choo Chung: Journal of informations science and engineering. 17(2001)713–727.

Google Scholar

[4] Yong Zhao, Zongde Fang, Kanwei Wang, Hui Pang, Multilevel minimum cross entropy threshold selection based on quantum particle swarm optimization, In Proceeding of 8th ICSEAINPC. (2007) 65–69.

DOI: 10.1109/snpd.2007.85

Google Scholar

[5] Zhiwei Ye, Hongwei Chen, Wei Liu, Jinping Zhang, Automatic threshold selection based on particle swarm optimization algorithm, In Proceedings of international conference on intelligent computation technology and automation. (2008)36–39.

DOI: 10.1109/icicta.2008.51

Google Scholar

[6] Xin-She Yang. Firefly algorithms for multimodal optimization, Stochastic Algorithms: Foundations and Applications, SAGA 2009. Lecture Notes in Computer Sciences. 5792(2009) 169–178.

DOI: 10.1007/978-3-642-04944-6_14

Google Scholar

[7] Lukasik, S., Zak, S, Firefly algorithm for continuous constrained optimization task, ICCCI 2009, Lecture Notes in Artificial Intelligence. 5796(2009) 97-100.

Google Scholar

[8] Ming-Huwi Horng, Ren-Jean Liou: Expert Systems with Applications. 38(2011)14805-14811.

Google Scholar