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A Technique to Reduce the Processing Time of Defect Detection in Glass Tubes

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Intelligent Computing (CompCom 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 997))

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Abstract

The evolution of the glass production process requires high accuracy in defects detection and faster production lines. Both requirements result in a reduction in the processing time of defect detection in case of real-time inspection. In this paper, we present an algorithm for defect detection in glass tubes that allows such reduction. The main idea is based on the reduce the image areas to investigate by exploiting the features of images. In our experiment, we utilized two algorithms that have been successfully applied in the inspection of pharmaceutical glass tube: Canny algorithm and MAGDDA. The proposed solution, applied on both algorithms, doesn’t compromise the quality of detection and allows us to achieve a performance gain of 66% in terms of processing time, and 3 times in term of throughput (frames per second), in comparison with standard implementations. An automatic procedure has been developed to estimate optimal parameters for the algorithm by considering the specific production process.

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Acknowledgments

This work has been partially supported by the Italian Ministry of Education and Research (MIUR) in the framework of the CrossLab project (Departments of Excellence – LAB Advanced Manufacturing and LAB Cloud Computing, Big data & Cybersecurity).

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Authors and Affiliations

  1. Dipartimento di Ingegneria dell’Informazione, Università di Pisa, Pisa, Italy

    Gabriele Antonio De Vitis, Pierfrancesco Foglia & Cosimo Antonio Prete

Authors
  1. Gabriele Antonio De Vitis
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  2. Pierfrancesco Foglia
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  3. Cosimo Antonio Prete
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Corresponding author

Correspondence to Gabriele Antonio De Vitis .

Editor information

Editors and Affiliations

  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

  2. The Science and Information SAI Organization, Bradford, West Yorkshire, UK

    Rahul Bhatia

  3. The Science and Information SAI Organization, Bradford, West Yorkshire, UK

    Supriya Kapoor

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De Vitis, G.A., Foglia, P., Prete, C.A. (2019). A Technique to Reduce the Processing Time of Defect Detection in Glass Tubes. In: Arai, K., Bhatia, R., Kapoor, S. (eds) Intelligent Computing. CompCom 2019. Advances in Intelligent Systems and Computing, vol 997. Springer, Cham. https://doi.org/10.1007/978-3-030-22871-2_13

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