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International Symposium on Visual Computing

ISVC 2015: Advances in Visual Computing pp 355–364Cite as

Ice Detection on Electrical Power Cables

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9475))

Abstract

In northern countries, ice storms can cause major power disruptions such as the one that occurred on December 2013 that left more than 300,000 customers in Toronto with no electricity immediately after such an ice storm. Detection of ice formation on power cables can help on taking actions for removing the ice before a major problem occurs. A computer vision solution was developed to detect ice on difficult imaging scenarios such as images taken under fog conditions that reduces the image contrast, passing cars that are within the field of view of the camera as well as different illumination problems that can occur when taking images during different times of the day. Based on a neural network for classification and six image features that can deal with these difficult images, we reduced the errors on a set of images that was previously yielding 20 errors out of 50 images to only one error.

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Author information

Authors and Affiliations

  1. Electrical and Computer Engineering Department, University of Manitoba, Winnipeg, MB, Canada

    Binglin Li & Gabriel Thomas

  2. Manitoba HVDC Centre, Winnipeg, MB, Canada

    Dexter Williams

Authors
  1. Binglin Li
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  2. Gabriel Thomas
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  3. Dexter Williams
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Corresponding author

Correspondence to Gabriel Thomas .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. University of Houston, Houston, Texas, USA

    Ioannis Pavlidis

  6. IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Rogerio Feris

  7. Purdue University, West Lafayette, Indiana, USA

    Tim McGraw

  8. Side Effects Software, Santa Monica, California, USA

    Mark Elendt

  9. The DiVE, Durham, North Carolina, USA

    Regis Kopper

  10. Texas A&M University, College Station, Texas, USA

    Eric Ragan

  11. Kent State University, Kent, Ohio, USA

    Zhao Ye

  12. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Gunther Weber

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© 2015 Springer International Publishing Switzerland

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Cite this paper

Li, B., Thomas, G., Williams, D. (2015). Ice Detection on Electrical Power Cables. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9475. Springer, Cham. https://doi.org/10.1007/978-3-319-27863-6_33

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  • DOI: https://doi.org/10.1007/978-3-319-27863-6_33

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27862-9

  • Online ISBN: 978-3-319-27863-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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