Machine Vision and Applications

, Volume 12, Issue 4, pp 177–188

Machine vision system for curved surface inspection

  • Min-Fan Ricky Lee
  • Clarence W. de Silva
  • Elizabeth A. Croft
  • Q.M. Jonathan Wu
Special Issue: High Performance Computing for Industrial Visual Inspection

DOI: 10.1007/s001380000043

Cite this article as:
Lee, MF., de Silva, C., Croft, E. et al. Machine Vision and Applications (2000) 12: 177. doi:10.1007/s001380000043

Abstract.

This application-oriented paper discusses a non-contact 3D range data measurement system to improve the performance of the existing 2D herring roe grading system. The existing system uses a single CCD camera with unstructured halogen lighting to acquire and analyze the shape of the 2D shape of the herring roe for size and deformity grading. Our system will act as an additional system module, which can be integrated into the existing 2D grading system, providing the additional third dimension to detect deformities in the herring roe, which were not detected in the 2D analysis. Furthermore, the additional surface depth data will increase the accuracy of the weight information used in the existing grading system. In the proposed system, multiple laser light stripes are projected into the herring roe and the single B/W CCD camera records the image of the scene. The distortion in the projected line pattern is due to the surface curvature and orientation. Utilizing the linear relation between the projected line distortion and surface depth, the range data was recovered from a single camera image.

The measurement technique is described and the depth information is obtained through four steps: (1) image capture, (2) stripe extraction, (3) stripe coding, (4) triangulation, and system calibration. Then, this depth information can be converted into the curvature and orientation of the shape for deformity inspection, and also used for the weight estimation.

Preliminary results are included to show the feasibility and performance of our measurement technique. The accuracy and reliability of the computerized herring roe grading system can be greatly improved by integrating this system into existing system in the future.

Key words: Structured light – 3D sensing – Range sensing – Inspection – Computer vision 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Min-Fan Ricky Lee
    • 1
  • Clarence W. de Silva
    • 1
  • Elizabeth A. Croft
    • 2
  • Q.M. Jonathan Wu
    • 1
  1. 1.National Research Council Canada, Integrated Manufacturing Technology Institute – West 3250 East Mall, Vancouver, BC V6T 1W5, Canada; Tel: 604-221-3051; Fax: 604-221-3001; e-mail: ricky.lee@nrc.caCA
  2. 2.Industrial Automation Laboratory, Department of Mechanical Engineering, University of British Columbia. 2324 Main Mall Vancouver, BC, Canada V6T 1Z4CA

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