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Defect Detection of Alumina Substrate with Adaptive Edge Detection Algorithm

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Cloud Computing and Security (ICCCS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11068))

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Abstract

Detecting surface defects of alumina substrate by using computer technique will enhance productivity in industrial manufacture. Edge detection of image is the commonly used technique for the detection of surface defects. However, it is difficult to automatically detect the surface defects of the alumina substrate since the noise and the multiple kinds of defects may exist in a substrate. In this paper, we designed an edge detection algorithm based on Canny detector aiming to automatically detect the surface defects of alumina substrate. Our algorithm can adaptively smooth image as well as adaptively determine the low threshold and high threshold. Experiments show that our algorithm can effectively and automatically detect several kinds of surface defects in the alumina substrate.

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Acknowledgements

This work is supported by the China Postdoctoral Science Foundation (No. 2016M602675), the Foundation of Central Universities in China (No. ZYGX2016J123), and the Project of Education Department of Sichuan Province (No. 16ZA0328), PhD research startup foundation of Yibin University (No. 2015QD08), and Sichuan Science and Technology Program (No. 2018JY0117).

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Authors and Affiliations

  1. Center for Information in BioMedicine, Key Laboratory for Neuroinformation of Ministry of University of Electronic Science and Technology, Chengdu, China

    Chaorong Li

  2. Department of Computer Science and Information Engineering, Yibin University, Yibin, 644000, China

    Chaorong Li & Lihong Zhu

  3. Department of Information and Engineering, Chengdu Aeronautic Vocational and Technical College, Chengdu, 610100, China

    Liangwei Chen

  4. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, China

    Yu Xue

Authors
  1. Chaorong Li
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  2. Liangwei Chen
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  3. Lihong Zhu
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  4. Yu Xue
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Corresponding author

Correspondence to Chaorong Li .

Editor information

Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. Nanjing University of Information Science and Technology, Nanjing, China

    Zhaoqing Pan

  3. Department of Computer Science, Purdue University, West Lafayette, IN, USA

    Elisa Bertino

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Li, C., Chen, L., Zhu, L., Xue, Y. (2018). Defect Detection of Alumina Substrate with Adaptive Edge Detection Algorithm. In: Sun, X., Pan, Z., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2018. Lecture Notes in Computer Science(), vol 11068. Springer, Cham. https://doi.org/10.1007/978-3-030-00021-9_44

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  • DOI: https://doi.org/10.1007/978-3-030-00021-9_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-00020-2

  • Online ISBN: 978-3-030-00021-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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