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Pin Defect Inspection with X-ray Images

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Advances in Neural Networks - ISNN 2017 (ISNN 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10262))

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Abstract

A method of Printed Circuit Board (PCB) pin defect inspection is proposed in this paper. First, we input the pin location image. Then, we align images with Circle Hough Transform (CHT) [4]. Finally, we train cascade classifier with adaptive boosting [3] and Local Binary Pattern (LBP) [5], and detect pin defect to reduce false alarm rate and miss detection rate and thus enhance pin production yield rate.

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References

  1. Rosebrock, A.: Local Binary Patterns with Python & OpenCV (2016). http://www.pyimagesearch.com/2015/12/07/local-binary-patterns-with-python-opencv/

  2. Read01.com: Machine Learning (2016). https://read01.com/Dngkd.html

  3. Wikipedia: AdaBoost (2016). https://en.wikipedia.org/wiki/AdaBoost

  4. Wikipedia: Circle Hough Transform (2016). https://en.wikipedia.org/wiki/Circle_Hough_Transform

  5. Wikipedia: Local Binary Pattern (2016). https://en.wikipedia.org/wiki/Local_binary_patterns

  6. Wikipedia: Visual Descriptor (2016). https://en.wikipedia.org/wiki/Visual_descriptor

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Acknowledgement

This research was supported by the Ministry of Science and Technology of Taiwan, R.O.C., under grants MOST 103-2221-e-002-188 and 104-2221-e-002-133-my2, and by Test Research (TRI), Liteon, Egistec, Delta Electronics, and Lumens Digital Optics.

Author information

Authors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan

    Hsien-Pei Kao, Tzu-Chia Tung, Hong-Yi Chen & Chiou-Shann Fuh

  2. Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan

    Cheng-Shih Wong & Chiou-Shann Fuh

Authors
  1. Hsien-Pei Kao
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  2. Tzu-Chia Tung
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  3. Hong-Yi Chen
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  4. Cheng-Shih Wong
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  5. Chiou-Shann Fuh
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Corresponding author

Correspondence to Chiou-Shann Fuh .

Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Fengyu Cong

  2. City University of Hong Kong, Kowloon Tong, Hong Kong

    Andrew Leung

  3. Chinese Academy of Sciences, Beijing, China

    Qinglai Wei

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Kao, HP., Tung, TC., Chen, HY., Wong, CS., Fuh, CS. (2017). Pin Defect Inspection with X-ray Images. In: Cong, F., Leung, A., Wei, Q. (eds) Advances in Neural Networks - ISNN 2017. ISNN 2017. Lecture Notes in Computer Science(), vol 10262. Springer, Cham. https://doi.org/10.1007/978-3-319-59081-3_54

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  • DOI: https://doi.org/10.1007/978-3-319-59081-3_54

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59080-6

  • Online ISBN: 978-3-319-59081-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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