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International Workshop on Combinatorial Image Analysis

IWCIA 2018: Combinatorial Image Analysis pp 216–226Cite as

Defect Detection in Textiles with Co-occurrence Matrix as a Texture Model Description

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Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 11255))

Abstract

Automatized inspection at textile production lines becomes very important. However, there is still a need to design methods which meet not only demands concerning accuracy of defect detection, but also ones related to the processing time. In this work, a novel approach for defect model definition is presented. It is derived from the idea of co-occurrence matrix. Due to scale incorporation and binarization of the model content it proved to be a very powerful descriptor of the novelties. Moreover, it also satisfies the requirements of short processing time. The defect mask achieved with the introduced method was compared visually to other popular solutions and show a very high accuracy and quality of defect description. The processing time is real-time as the response for a 1MP (megapixel) image is reached within tens of milliseconds.

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Acknowledgements

This work has been based on the results of the project “Opracowanie systemu do efektywnej integracji aplikacji wizyjnych przez użyt- kowników końcowych” co-financed by the European Regional Development Fund under Operational Programme Innovative Economy 2007–2013, based on the Agreement no. UDA-POIG.01.04.00-24-067/11-00.

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Authors and Affiliations

  1. Future Processing Sp. z o.o., ul. Bojkowska 37A, 44-100, Gliwice, Poland

    Karolina Nurzynska & Michał Czardybon

  2. Institute of Informatics, Silesian University of Technology, ul. Akademicka 16, 44-100, Gliwice, Poland

    Karolina Nurzynska

Authors
  1. Karolina Nurzynska
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  2. Michał Czardybon
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Corresponding author

Correspondence to Karolina Nurzynska .

Editor information

Editors and Affiliations

  1. State University of New York at Fredonia, Fredonia, NY, USA

    Reneta P. Barneva

  2. State University of New York, Buffalo, NY, USA

    Valentin E. Brimkov

  3. University of Porto, Porto, Portugal

    João Manuel R.S. Tavares

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Nurzynska, K., Czardybon, M. (2018). Defect Detection in Textiles with Co-occurrence Matrix as a Texture Model Description. In: Barneva, R., Brimkov, V., Tavares, J. (eds) Combinatorial Image Analysis. IWCIA 2018. Lecture Notes in Computer Science(), vol 11255. Springer, Cham. https://doi.org/10.1007/978-3-030-05288-1_17

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  • DOI: https://doi.org/10.1007/978-3-030-05288-1_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05287-4

  • Online ISBN: 978-3-030-05288-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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