Call for Paper - November 2021 Edition
IJCA solicits original research papers for the November 2021 Edition. Last date of manuscript submission is October 20, 2021. Read More

Measurement of Circular Saw Blade Tooth Dimensions based on Machine Vision

Print
PDF
IJCA Proceedings on International Conference on Recent Trends in Science, Technology, Management and Social Development
© 2019 by IJCA Journal
ICRTSTMSD 2018 - Number 1
Year of Publication: 2019
Authors:
Cheng-ho Chen
Wei-chao Lin

Cheng-ho Chen and Wei-chao Lin. Article: Measurement of Circular Saw Blade Tooth Dimensions based on Machine Vision. IJCA Proceedings on International Conference on Recent Trends in Science, Technology, Management and Social Development ICRTSTMSD 2018(1):1-4, August 2019. Full text available. BibTeX

@article{key:article,
	author = {Cheng-ho Chen and Wei-chao Lin},
	title = {Article: Measurement of Circular Saw Blade Tooth Dimensions based on Machine Vision},
	journal = {IJCA Proceedings on International Conference on Recent Trends in Science, Technology, Management and Social Development},
	year = {2019},
	volume = {ICRTSTMSD 2018},
	number = {1},
	pages = {1-4},
	month = {August},
	note = {Full text available}
}

Abstract

Machine vision is a non-contact sensing technology, which has been widely used in various applications, e. g. automatic inspection and robot guidance, in recent years. A basic machine vision system consists of a camera, a frame grabber, a computer, an illuminant source and image processing software. This research studies the application of machine vision for the measurement of tooth dimensions of a circular saw blade. Through backlit illumination, a CCD camera captured the image of the saw blade tooth. The image is then processed and analyzed for the tooth radius and depth. The results are compared with those obtained by an automatic precision measuring instrument (M-V Vertex 410) to verify the accuracy and precision of the machine vision system.

References

  • T. Kido, "In-process Inspection Technique for Active-matrix LCD Panels", International Test Conference, pp. 795-799, 1992.
  • S. Kurada and C. Bradley, "A review of machine vision sensor for tool condition monitoring", Computers in Industry, vol. 34, pp. 52~72, 1997.
  • J. Li, Y. Guo, J. Zhu, X. Lin, Y. Xin, K. Duan, and Qing Tang, "Large depth-of-view portable three-dimensional laser scanner and its segmental calibration for robot vision", Optics and Lasers in Engineering, vol. 45, pp. 1077-1087, 2007.
  • M. Szyd?owskia, B. Powa?kaa, M. Matuszakb, and P. Kochma´nski, "Machine vision micro-milling tool wear inspection by image reconstruction and light reflectance", Precision Engineering, vol. 44, pp. 236-244. 2016.
  • E. S. Gadelmawla, "Computer vision algorithms for measurement and inspection of external screw threads", Measurement, vol. 100, pp. 36-49, 2017.
  • P. Liu and B. H. Shi, "The Measuring System for Flat Degree of Circular Saw Based on LabVIEW", Microcomputer Information, ??????, vol. 23, no. 25, pp. 140-142, 2007.
  • L. Zhao, Q. Liu, and W. Dai, "Precision visual measurement on geometry parameters of circular saw blade", Infrared and Laser Engineering, ???????, vol. 39, no. 6, pp. 1115-1119, Dec. 2010.
  • Y. -C. Wang, J. -C. Lin, and S. -F. Chiu, "The automatic image inspection system for measuring dimensional parameters of a saw blade", 8th IEEE International Conference on Control & Automation (ICCA 10), IEEE Control Systems Chapter, Singapore, Xiamen, pp. 1557 – 1561, 2010.
  • J. S. Weszka, "A survey of threshold selection techniques", Computer Graphics and Image Processing, vol. 7, issue 2, pp. 259-265, 1978.
  • R. Kateeyare1 and P. Baga, "A Survey on Object Removal and Region Filling In Image", International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, vol. 5, pp. 7581-7582, 2016.
  • L. Wei and Z. Jiao, "Visual Location System for Placement Machine based on Machine Vision", Fifth IEEE International Symposium on Embedded Computing, pp. 141-146, 2008.
  • J. C. Su, C. K. Huang and Y. S. Tarng, "An automated flank wear measurement of microdrills using machine vision", Journal of Materials Processing Technology, vol. 180, pp. 328-335, 2006.