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Vision Diagnostics of Power Transmission Lines: Approach to Recognition of Insulators

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Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 403))

Abstract

Due to requirements related to the maintenance of power transmission lines, it is necessary to diagnose their condition regularly. Among approaches being nowadays applied fundamental technical diagnostic methods are the vision inspections, often performed with use of cameras. The aim of this paper is to develop a method of automated recognition of insulators in images for the purposes of further computer analysis of their technical condition. Application of image segmentation by the statistical region merging method lets separate objects visible in images of very composed backgrounds. In order to recognize the insulators the template matching by an improved brute force method was used. The author proposes an approach which makes use of the fact that insulators are longitudinal and the problem with scaling and rotation variability is solved. The proposed algorithm can be applied to automatic recognition of insulators as well as any oblong elements in images.

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References

  1. Ahmad, J., Malik, A.S., Xia, L., Ashikin, N.: Vegetation Encroachment monitoring for transmission lines right-of-ways: a survey. Electr. Pow. Syst. Res. 95, 339–352 (2013)

    Article  Google Scholar 

  2. Bagavathiappan, S., Lahiri, B.B., Saravanan, T., Philip, J., Jayakumar, T.: Infrared thermography for condition monitoring—a review. Infrared Phys. Techn. 60, 35–55 (2013)

    Article  Google Scholar 

  3. Gonçalves, R.S., Carvalho, J.C.M.: Review and latest trends in mobile robots used on power transmission lines. Int. J. Adv. Robot. Syst 10(408), 1–14 (2013)

    Google Scholar 

  4. Silva, K.M., Souza, B.A., Brito, N.S.D.: Fault detection and classification in transmission lines based on wavelet transform and ANN. IEEE T. Power Deliver. 21(4), 2058–2063 (2006)

    Article  Google Scholar 

  5. Bockarjova, M., Sauhats, A., Andersson, G.: Statistical algorithms for fault location on power transmission lines. In: IEEE Russia Power Tech 2005, pp. 1–7, St. Petersburg (2005)

    Google Scholar 

  6. Saadabad, N.A., Moradi, H., Vossoughi, G.: Semi-active control of forced oscillations in power transmission lines via optimum tuneable vibration absorbers: with review on linear dynamic aspects. Int. J. Mech. Sci. 87, 163–178 (2014)

    Article  Google Scholar 

  7. Tadeusiewicz, R., Wszołek, T., Izworski, A., Wszołek, W.: Recognition of defects in high voltage transmission lines using the acoustic signal of corona effect. In: Proceedings of the 2000 IEEE Signal Processing Society Workshop., Neural Networks for Signal Processing X (2)NSW, Sydney, pp. 869–875 (2000)

    Google Scholar 

  8. Current and future UAV military users and applications. Air & Space Europe 1(5–6), 51–58 (1999)

    Google Scholar 

  9. Metni, N., Hamel, T.: A UAV for bridge inspection: visual servoing control law with orientation limits. Automat. Constr. 17, 3–10 (2007)

    Article  Google Scholar 

  10. Aibot X6 Multicopter for Mapping and Industry—Aibotix International, www.aibotix.com

  11. Roca, D., Lagüela, S., Díaz-Vilariño, L., Armesto, J., Arias, P.: Low-cost aerial unit for outdoor inspection of building façades. Automat. Constr. 36, 128–135 (2013)

    Article  Google Scholar 

  12. Siebert, S., Teizer, J.: Mobile 3D mapping for surveying earthwork projects using an unmanned aerial vehicle (UAV) system. Automat. Constr. 41, 1–14 (2014)

    Article  Google Scholar 

  13. Li, Z., Liu, Y., Walker, R., Hayward, R., Zhang, J.: Towards automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved hough transform. Mach. Vis. Appl. 21(5), 677–686 (2010)

    Article  Google Scholar 

  14. Rajeev, M.B., Adithya, V., Hrishikesh, S., Balamurali, P.: Detection of power-lines in complex natural surroundings. Comput. Sci. Inf. Technol. (CS & IT) 3(9), 101–108 (2013)

    Google Scholar 

  15. Candamo, J., Kasturi, R., Goldgof, D., Sarkar, S.: Detection of thin lines using low-quality video from low-altitude aircraft in urban settings. IEEE T. Aero. Elec. Sys. 45(3), 937–949 (2009)

    Article  Google Scholar 

  16. Song, B., Li, X.: Power line detection from optical images. Neurocomputing 129, 350–361 (2014)

    Article  Google Scholar 

  17. Liu, G., Zhu, Z., Jie, X.: Orientation and damage inspection of insulators based on tchebichef moment invariants. In: IEEE 2008 International Conference on Neural Networks & Signal Processing, pp. 48–52, Zhenjiang, China (2008)

    Google Scholar 

  18. Shinohara, A.H., Santana, D.M.F., Oliveira, P.P.J.C., Silva, R.J.G., Magalhães, O.H., Silveira, C.G., Khoury, H.J., Wavrik, J.F.A.G., Branco, F.M.A.C., Leite, M.A., Galindo, T.C.: Defects detection in electrical insulators and breaker for high voltage by low cost computed radiography systems. In: International Symposium on Digital industrial Radiology and Computed Tomography. Lyon, France (2007)

    Google Scholar 

  19. Wronkowicz, A.: Concept of diagnostics of energy networks by means of vision system. Diagnostyka 15(2), 13–18 (2014)

    Google Scholar 

  20. Pratt, W.K.: Digital Image Processing: PIKS Scientific Inside, 4th edn. Willey-Interscience, Hoboken (2007)

    Book  MATH  Google Scholar 

  21. Gonzalez, R.C., Woods, R.E., Eddins, S.L.: Digital Image Processing using MATLAB, 2nd edn. Gatesmark Publishing, Knoxville (2009)

    Google Scholar 

  22. Sonka, M., Hlavac, V., Boyle, R.: Image Processing, Analysis, and Machine Vision, 4th edn. Cengage Learning, Stamford (2014)

    Google Scholar 

  23. Ventura, A.S., Borrego, J.Á., Solorza, S.: Adaptive nonlinear correlation with a binary mask invariant to rotation and scale. Opt. Commun. 339, 185–193 (2015)

    Article  Google Scholar 

  24. Torres-Méndez, L.A., Ruiz-Suárez, J.C., Sucar, L.E., Gómez, G.: Translation, rotation and scale-invariant object recognition. IEEE Trans. Systems, Man, and Cybernetics—part C: Applications and Reviews 30(1), 125–130 (2000)

    Google Scholar 

  25. Tsai, D.-M., Chiang, C.-H.: Rotation-invariant pattern matching using wavelet decomposition. Pattern Recog. Lett. 23(1–3), 191–201 (2002)

    Article  MATH  Google Scholar 

  26. Liao, S.X., Pawlak, M.: On image analysis by moments. IEEE T. Pattern Anal. 18(3), 254–266 (1996)

    Article  Google Scholar 

  27. Reddy, B.S., Chatterji, B.N.: An FFT-based technique for translation, rotation, and scale-invariant image registration. IEEE Trans. Image Process. 5(8), 1266–1271 (1996)

    Article  Google Scholar 

  28. Nock, R., Nielsen, F.: Statistical region merging. IEEE T. Pattern. Anal. 26(11), 1452–1458 (2004)

    Article  Google Scholar 

  29. Lewis, J.P.: Fast normalized cross-correlation. Vis. Interface 10(1), 120–123 (1995)

    Google Scholar 

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Correspondence to Angelika Wronkowicz .

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Wronkowicz, A. (2016). Vision Diagnostics of Power Transmission Lines: Approach to Recognition of Insulators. In: Burduk, R., Jackowski, K., Kurzyński, M., Woźniak, M., Żołnierek, A. (eds) Proceedings of the 9th International Conference on Computer Recognition Systems CORES 2015. Advances in Intelligent Systems and Computing, vol 403. Springer, Cham. https://doi.org/10.1007/978-3-319-26227-7_40

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  • DOI: https://doi.org/10.1007/978-3-319-26227-7_40

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-26225-3

  • Online ISBN: 978-3-319-26227-7

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