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A Vision-Based Wheel Disc Inspection System

  • Huu-Cuong NguyenEmail author
  • Phuoc-Loc Nguyen
  • Byung-Ryong Lee
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 63)

Abstract

An automated based-vision quality inspection system for wheel-disc is presented in this paper in order to achieve nondestructive and fast defect detection method. The system captures images of wheel-disc which is located on a backlight device. Using these image data, holes in wheel-disc image are detected by ellipse detection algorithm. After that the size and positions of holes on real wheel-disc can be obtained in real time. Experimental results show that although the proposed system is fairly simple, it achieves high accuracy and reliability for wheel disc defect detection.

Keywords

Wheel disc Defect detection Inspection system Image processing Ellipse fitting 

References

  1. 1.
    Juen, K., Ki, B.L., Jaeyeon, J., Kyong, S.C., Chang, O.K.: Automatic inspection of salt-and-pepper defects in OLED panels using image processing and control chart techniques. J. Intell. Manuf. 28(1), 1–9 (2017)CrossRefGoogle Scholar
  2. 2.
    Hui, H.C., Zong, Y.W.: A study on welding quality inspection system for shell-tube heat exchanger based on machine vision. Int. J. Precis. Eng. Manuf. 18(6), 825–834 (2017)CrossRefGoogle Scholar
  3. 3.
    Yang, Y., Chen, S.: An online detection system for aggregate sizes and shapes based on digital image processing. Mineral. Petrol. 111(1), 135–144 (2017)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Zhang, H., Li, X., Zhong, H., Yang, Y., Wu, Q.M.J., Ge, J., Wang, Y.: Automated machine vision system for liquid particle inspection of pharmaceutical injection. IEEE Trans. Instrum. Meas. 67(6), 1278–1297 (2018)CrossRefGoogle Scholar
  5. 5.
    Shen, H., Li, S., Gu, D., Chang, H.: Bearing defect inspection based on machine vision. Measurement 45(4), 719–733 (2012)CrossRefGoogle Scholar
  6. 6.
    Leister, G.: Passenger Car Tires and Wheels: Development – Manufacturing - Application. Springer (2018)Google Scholar
  7. 7.
    Andrew, W.F., Robert, B.F.: A buyer’s guide to conic fitting. In: Proceeding of the 6th British Conference on Machine Vision, MBVC 1995, vol. 2, pp. 513–522. Birmingham, United Kingdom (1995)Google Scholar
  8. 8.
    John, C.: A computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8(6), 679–698 (1986)Google Scholar
  9. 9.
    Zhang, Z.: A flexible new technique for camera calibration. IEEE Trans. Pattern Anal. Mach. Intell. 22(11), 1330–1334 (2000)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Huu-Cuong Nguyen
    • 1
    Email author
  • Phuoc-Loc Nguyen
    • 2
  • Byung-Ryong Lee
    • 3
  1. 1.Can Tho UniversityCan ThoVietnam
  2. 2.Kien Giang Vocational CollegeRach GiaVietnam
  3. 3.University of UlsanUlsanKorea

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