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A Survey of Computer Vision Based Corrosion Detection Approaches

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Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 2 ( ICTIS 2017)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 84))

Abstract

There are various destructive as well as non-destructive techniques available to detect corrosion in metallic surfaces. Digital Image Processing is widely being used for the corrosion detection in metallic surface. This non-destructive approach provides cost effective, fast and reasonably accurate results. Several algorithms have been developed by different researchers and research groups for detecting corrosion using digital image processing techniques. Several algorithms related to color, texture, noise, clustering, segmentation, image enhancement, wavelet transformation etc. have been used in different combinations for corrosion detection and analysis. This paper reviews the different image processing techniques and the algorithms developed and used by researchers in various industrial applications.

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Authors and Affiliations

  1. AIIT, Amity University, Noida, Uttar Pradesh, India

    Sanjay Kumar Ahuja

  2. ASET, Amity University, Noida, Uttar Pradesh, India

    Manoj Kumar Shukla

Authors
  1. Sanjay Kumar Ahuja
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  2. Manoj Kumar Shukla
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Corresponding author

Correspondence to Sanjay Kumar Ahuja .

Editor information

Editors and Affiliations

  1. Department of CSE, PVP Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, India

    Suresh Chandra Satapathy

  2. Sabar Institute of Technology for Girls, Ahmedabad, Gujarat, India

    Amit Joshi

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Ahuja, S.K., Shukla, M.K. (2018). A Survey of Computer Vision Based Corrosion Detection Approaches. In: Satapathy, S., Joshi, A. (eds) Information and Communication Technology for Intelligent Systems (ICTIS 2017) - Volume 2. ICTIS 2017. Smart Innovation, Systems and Technologies, vol 84. Springer, Cham. https://doi.org/10.1007/978-3-319-63645-0_6

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  • DOI: https://doi.org/10.1007/978-3-319-63645-0_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63644-3

  • Online ISBN: 978-3-319-63645-0

  • eBook Packages: EngineeringEngineering (R0)

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