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Multi-camera Vision System for the Inspection of Metal Shafts

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Book cover Challenges in Automation, Robotics and Measurement Techniques (ICA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 440))

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Abstract

To address the needs of the manufacturing industry, the automation of quality inspection processes is often performed. Ensuring the high reliability and accuracy of measurement usually requires the development of specialized systems dedicated for specific applications. In the paper, a multi-camera vision system developed for the automatic inspection of metal shafts in the automotive industry is presented. The novel solution of the inspection system is based on the application of a set of three cameras that allow the inspection of shafts in separated areas. The system enables the detection and recognition of the following features: thread, knurls, grooves, and measurements of the shaft length. The image processing is performed with the use of filtering, morphology operations (dilation and erosion), and edge detection. The two-dimensional Look-up Table has been created in order to calculate a correct shaft length considering perspective errors of lenses.

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Author information

Authors and Affiliations

  1. Instytut Technologii Eksploatacji – Państwowy Instytut Badawczy, Radom, Poland

    Piotr Garbacz & Tomasz Giesko

Authors
  1. Piotr Garbacz
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  2. Tomasz Giesko
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Corresponding author

Correspondence to Piotr Garbacz .

Editor information

Editors and Affiliations

  1. Automation and Measurements PIAP, Industrial Research Institute for, Warsaw, Poland

    Roman Szewczyk

  2. Automation and Measurements PIAP, Industrial Research Institute for, Warsaw, Poland

    Cezary Zieliński

  3. Automation and Measurements PIAP, Industrial Research Institute for, Warsaw, Poland

    Małgorzata Kaliczyńska

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Garbacz, P., Giesko, T. (2016). Multi-camera Vision System for the Inspection of Metal Shafts. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Challenges in Automation, Robotics and Measurement Techniques. ICA 2016. Advances in Intelligent Systems and Computing, vol 440. Springer, Cham. https://doi.org/10.1007/978-3-319-29357-8_64

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  • DOI: https://doi.org/10.1007/978-3-319-29357-8_64

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29356-1

  • Online ISBN: 978-3-319-29357-8

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