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Industrial Inspection with Open Eyes: Advance with Machine Vision Technology

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Integrated Imaging and Vision Techniques for Industrial Inspection

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

Machine vision systems have evolved significantly with the technology advances to tackle the challenges from modern manufacturing industry. A wide range of industrial inspection applications for quality control are benefiting from visual information captured by different types of cameras variously configured in a machine vision system. This chapter screens the state of the art in machine vision technologies in the light of hardware, software tools, and major algorithm advances for industrial inspection. The inspection beyond visual spectrum offers a significant complementary to the visual inspection. The combination with multiple technologies makes it possible for the inspection to achieve a better performance and efficiency in varied applications. The diversity of the applications demonstrates the great potential of machine vision systems for industry.

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Authors and Affiliations

  1. University of British Columbia Okanagan, Kelowna, British Columbia, Canada

    Zheng Liu

  2. Tokushima University, Tokushida, Japan

    Hiroyuki Ukida

  3. University of Applied Sciences Upper Austria (Campus Wels), Wels, Austria

    Kurt Niel

  4. Pacific Northwest National Laboratory, Richland, WA, USA

    Pradeep Ramuhalli

Authors
  1. Zheng Liu
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  2. Hiroyuki Ukida
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  3. Kurt Niel
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  4. Pradeep Ramuhalli
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Correspondence to Zheng Liu .

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Editors and Affiliations

  1. University of British Columbia, Kelowna, BC, Canada

    Zheng Liu

  2. University of Tokushima, Tokushima, Japan

    Hiroyuki Ukida

  3. Pacific Northwest National Laboratory, Richland, WA, USA

    Pradeep Ramuhalli

  4. University of Applied Sciences Upper Austria, Wels, Austria

    Kurt Niel

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Liu, Z., Ukida, H., Niel, K., Ramuhalli, P. (2015). Industrial Inspection with Open Eyes: Advance with Machine Vision Technology. In: Liu, Z., Ukida, H., Ramuhalli, P., Niel, K. (eds) Integrated Imaging and Vision Techniques for Industrial Inspection. Advances in Computer Vision and Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-4471-6741-9_1

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  • DOI: https://doi.org/10.1007/978-1-4471-6741-9_1

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