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Integrated real-time measurement method of filament lamp dimension based on machine vision

Conference Paper


Abstract


  • An integrated method is proposed for the real-time measurement of filament lamp dimension based on machine vision (FLDMV). First, an online detection platform is built, and the image is acquired by telecentric lenses and charge-coupled diode (CCD). Second, a series of image processing, including filter, edge extraction, ellipse fitting, recursive minimum bounding rectangle, and curvature restrict estimation. Finally, the actual size of lamp is obtained by system calibration. The experimental analysis and comparison show that the maximum measurement error of this method is 0.21mm, which meets the requirements of filament lamp dimension measurement. The curvature restrict estimation based on ellipse fitting are proposed to guarantee the accuracy and real time. Compared with the traditional measurement method, our method has the advantages of fast measurement speed, high accuracy, and real time. It also can be widely used in other parts of the measurement.

UOW Authors


  •   Song, Limei (external author)
  •   Guo, Suqing (external author)
  •   Zhu, Xinjun (external author)
  •   Wang, Jiayan (external author)
  •   Guo, Qinghua
  •   Xi, Jiangtao
  •   Yang, Huaidong (external author)

Publication Date


  • 2017

Citation


  • L. Song, S. Guo, X. Zhu, J. Wang, Q. Guo, J. Xi & H. Yang, "Integrated real-time measurement method of filament lamp dimension based on machine vision," in AOPC 2017: 3D Measurement Technology for Intelligent Manufacturing, 2017, pp. 1045807-1-1045807-9.

Scopus Eid


  • 2-s2.0-85040534194

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/1029

Start Page


  • 1045807-1

End Page


  • 1045807-9

Place Of Publication


  • Washington, United States

Abstract


  • An integrated method is proposed for the real-time measurement of filament lamp dimension based on machine vision (FLDMV). First, an online detection platform is built, and the image is acquired by telecentric lenses and charge-coupled diode (CCD). Second, a series of image processing, including filter, edge extraction, ellipse fitting, recursive minimum bounding rectangle, and curvature restrict estimation. Finally, the actual size of lamp is obtained by system calibration. The experimental analysis and comparison show that the maximum measurement error of this method is 0.21mm, which meets the requirements of filament lamp dimension measurement. The curvature restrict estimation based on ellipse fitting are proposed to guarantee the accuracy and real time. Compared with the traditional measurement method, our method has the advantages of fast measurement speed, high accuracy, and real time. It also can be widely used in other parts of the measurement.

UOW Authors


  •   Song, Limei (external author)
  •   Guo, Suqing (external author)
  •   Zhu, Xinjun (external author)
  •   Wang, Jiayan (external author)
  •   Guo, Qinghua
  •   Xi, Jiangtao
  •   Yang, Huaidong (external author)

Publication Date


  • 2017

Citation


  • L. Song, S. Guo, X. Zhu, J. Wang, Q. Guo, J. Xi & H. Yang, "Integrated real-time measurement method of filament lamp dimension based on machine vision," in AOPC 2017: 3D Measurement Technology for Intelligent Manufacturing, 2017, pp. 1045807-1-1045807-9.

Scopus Eid


  • 2-s2.0-85040534194

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers1/1029

Start Page


  • 1045807-1

End Page


  • 1045807-9

Place Of Publication


  • Washington, United States