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The Ice Edge Detection of Transmission Line Based On Structured Forest Algorithm

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Proceedings of the Second International Conference on Mechatronics and Automatic Control

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 334))

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Abstract

Focusing on the existing problems of accuracy and latency in the current ice transmission line edge image detection, this chapter proposes a machine learning algorithm based on structured forest edge detection of ice transmission line. The ice transmission line image information’s model is automatically trained by the structured forest algorithm and the model is automatically applied for edge detection of the ice transmission line. Experimental results show that the method of ice transmission line edge detection is not only feasible and effective, but also can accurately detect ice line edge profile. What is more, it can meet the requirement of real time detection compared with other algorithms. Satisfactory results are obtained in the test.

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References

  1. Yi HU, Yi H. Analysis and countermeasures discussion for large area icing accident on power grid. High Volt Eng. 2008;34(2):001–2

    Google Scholar 

  2. XU S, ZHAO J. Review of ice storm cases impacted seriously on power systems and de-icing technology. South Power Syst Technol. 2008; 2(2):002–3

    Google Scholar 

  3. Davis LS. A survey of edge detection techniques. Computer Graph Image Process. 1975;4(3):248–70.

    Article  Google Scholar 

  4. Pal NR, Pal SK. A review on image segmentation techniques. Pattern Recognit. 1993;26(9):1277–94.

    Article  Google Scholar 

  5. Papari G, Petkov N. Edge and line oriented contour detection: State of the art. Image Vision Comput. 2011;29(2):79–103.

    Article  Google Scholar 

  6. Dollár P, Zitnick CL. Structured forests for fast edge detection.Computer Vision (ICCV), 2013 IEEE International Conference on. IEEE. 2013. p. 1841–48

    Google Scholar 

  7. Breiman L. Random forests. Mach Learn. 2001;45(1):5–32.

    Article  MATH  Google Scholar 

  8. KANG Y, Nagahashi H, Sugimoto H, et al. Image categorization using scene-context scale based on random forests. IEICE Trans Inf Syst. 2011;E94-D(9):1809–16.

    Article  Google Scholar 

  9. Yang BS, Di X, Han T. Random forests classifier for machine fault diagnosis. J Mech Sci Technol. 2008;22(9):1716–25.

    Article  Google Scholar 

  10. Taskar B, Chatalbashev V, Koller D, et al. Learning structured prediction models: A large margin approach. Proceedings of the 22nd international conference on Machine learning (ICML), 2005 IEEE International Conference on. IEEE. 2005. p. 896–903

    Google Scholar 

  11. Bowyer K, Kranenburg C, Dougherty S. Edge detector evaluation using empirical ROC curves. IEEE computer society conference on computer vision and pattern recognition, 1999. IEEE. 1999. 1:1–3

    Google Scholar 

  12. Tan RT. Visibility in bad weather from a single image. IEEE conference on computer vision and pattern recognition, 2008. CVPR 2008. IEEE. 2008. p. 1–8

    Google Scholar 

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Acknowledgements

This work was supported in part by the Fundamental Research Funds for the Central Universities Grant.

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Correspondence to Zhenyu Wang .

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© 2015 Springer International Publishing Switzerland

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Wang, Z., Jia, J., Teng, J. (2015). The Ice Edge Detection of Transmission Line Based On Structured Forest Algorithm. In: Wang, W. (eds) Proceedings of the Second International Conference on Mechatronics and Automatic Control. Lecture Notes in Electrical Engineering, vol 334. Springer, Cham. https://doi.org/10.1007/978-3-319-13707-0_45

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  • DOI: https://doi.org/10.1007/978-3-319-13707-0_45

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13706-3

  • Online ISBN: 978-3-319-13707-0

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