Automatic Calibration of the Optical System in Passive Component Inspection

Sungho Suh, Moonjoo Kim

Abstract

A passive component inspection machine is to obtain a image of a passive component by using a specific lighting and camera, and to detect defects on the image of the component. It inspects all the aspects of the component based on the image which is captured by using the lightings and cameras. The number of the lightings and cameras are proportional to the number of the component aspects. To detect the defects of the component effectively, the difference between the image quality by each camera should be minimized. Even if the light conditions are calibrated automatically, the average intensities of the images are different because of influence of Bayer filter which is used in CCD camera in the passive component inspection machine. Moreover, there is one more problem that the range of the light intensity cannot cover the range of the component reflectance. Sometimes, it is needed to calibrate a gain value and white balance ratios of the camera manually. In order to solve the problems, we propose an automatic calibration method of the optical system in passive component inspection machine. The proposed method minimizes the influence of Bayer filter, does not use any initial camera calibration, and find the optimal values for the overall gain and white balance ratios of red, green, blue colors automatically. To reduce the influence of Bayer filter, we perform to find the optimal values of all colors balance ratio iteratively and formulate a relation between the overall gain and the white balance ratios to control all the parameters automatically. The proposed method is simple and the experimental results show that the proposed method provides faster and more precise than the previous method.

References

  1. Basler Vision Technologies (2015). User Manual for GigE Cameras.
  2. chieh Tseng, C., fu Lai, M., and song Lee, P. (2006). Image Inspection System for Defect Detection of Multilayer Ceramic Capacitors. International Conference on Intelligent Information Hiding and Multimedia.
  3. chieh Tseng, C., Wu, J.-H., and Liao, B.-Y. (2009). Defect Detection of Skewed Images for Multilayer Ceramic Capacitors. International Conference on Intelligent Information Hiding and Multimedia Signal Processing.
  4. Hubel, P. M., Liu, J., and Guttosch, R. J. (2004). Spatial frequency response of color image sensors: Bayer color filters and Foveon X3. SPIE Electronic Imaging.
  5. Kim, D.-H., tae Bae, J., bok Kim, T., and hyeon Kim, G. (2013). Electrostatic inductive absorption type inspection table for electronic components.
  6. Liu, D., Braden, D., De, V. R. V., Hawkes, M. V., and Nebres, J. V. (2007). Inspection machine for surface mount passive component.
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Paper Citation


in Harvard Style

Suh S. and Kim M. (2017). Automatic Calibration of the Optical System in Passive Component Inspection . In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017) ISBN 978-989-758-225-7, pages 230-237. DOI: 10.5220/0006165402300237


in Bibtex Style

@conference{visapp17,
author={Sungho Suh and Moonjoo Kim},
title={Automatic Calibration of the Optical System in Passive Component Inspection},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)},
year={2017},
pages={230-237},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006165402300237},
isbn={978-989-758-225-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4: VISAPP, (VISIGRAPP 2017)
TI - Automatic Calibration of the Optical System in Passive Component Inspection
SN - 978-989-758-225-7
AU - Suh S.
AU - Kim M.
PY - 2017
SP - 230
EP - 237
DO - 10.5220/0006165402300237