High Precision Edge Detection Algorithm for Mechanical Parts

Open access

Abstract

High precision and high efficiency measurement is becoming an imperative requirement for a lot of mechanical parts. So in this study, a subpixel-level edge detection algorithm based on the Gaussian integral model is proposed. For this purpose, the step edge normal section line Gaussian integral model of the backlight image is constructed, combined with the point spread function and the single step model. Then gray value of discrete points on the normal section line of pixel edge is calculated by surface interpolation, and the coordinate as well as gray information affected by noise is fitted in accordance with the Gaussian integral model. Therefore, a precise location of a subpixel edge was determined by searching the mean point. Finally, a gear tooth was measured by M&M3525 gear measurement center to verify the proposed algorithm. The theoretical analysis and experimental results show that the local edge fluctuation is reduced effectively by the proposed method in comparison with the existing subpixel edge detection algorithms. The subpixel edge location accuracy and computation speed are improved. And the maximum error of gear tooth profile total deviation is 1.9 μm compared with measurement result with gear measurement center. It indicates that the method has high reliability to meet the requirement of high precision measurement.

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  • [1] Kumar B.M Ratnam M.M. (2015). Machine vision method for non-contact measurement of surface roughness of a rotating workpiece. Sensor Review 35 (1) 10-19.

  • [2] Gadelmawla E.S. (2011). Computer vision algorithms for measurement and inspection of spur gears. Measurement 44 (9) 1669-1678.

  • [3] Kosarevsky S. Latypov V. (2013). Detection of screw threads in computed tomography 3D density fields. Measurement Science Review 17 (2) 93-99.

  • [4] Robinson M.J. Oakley J.P. Cunningham M.J. (1995). The accuracy of image analysis methods in spur gear metrology. Measurement Science and Technology 6 860-871.

  • [5] Chen F. Brown G.M. (2000). Overview of threedimensional shape measurement using optical methods. Optical Engineering 39 (1) 10-21.

  • [6] Lu N.-G. Deng W.-Y. Wang Y.-Q. (2005). Profile measurement of microwave antenna using close range photogrammetry. In Third International Conference on Experimental Mechanics and Third Conference of the Asian Committee on Experimental Mechanics Proc. SPIE 5852 508-515.

  • [7] Sidor K. Szlachta A. (2017). The impact of the implementation of edge detection methods on the accuracy of automatic voltage reading. Measurement Science Review 13 (6) 292-297.

  • [8] Shang Y.-C. Chen J. Tian J.-W. (2010). The study of sub-pixel edge detection algorithm based on the function curve fitting. In 2nd International Conference on Information Engineering and Computer Science. IEEE 1-4.

  • [9] Wei B.-Z. Zhao Z.-M. (2013). A sub-pixel edge detection algorithm based on Zernike moments. The Imaging Science Journal 61 436-446.

  • [10] Liu G. Liu B. Chen F. Hu T. (2009). Study on the method of the accuracy evaluation of sub-pixel location operators. Acta Optica Sinica 29 3446-3451.

  • [11] Li S. Lu R. Shi Y. et al. (2011). Sub-pixel edge detection algorithm based on Gaussian Surface Fitting. Tool Engineer 45 79-82.

  • [12] Ma R. Zeng L. Lu Y. (2009). Improved sub-pixel edge detection based on Facet model. Journal of Basic Science and Engineering 17 296-302.

  • [13] Wang K. Zhang D. Huang H. et al. (2005). A study of sub voxel edge detection method based on 3-D Facet model. Mechanical Science and Technology 24 865-868.

  • [14] Xu L.-Y. Cao Z.-Q. Zhao P. Zhou C. (2017). A new monocular vision measurement method to estimate 3D positions of objects on floor. International Journal of Automation and Computing 14 159-168.

  • [15] Yu Q.-F. Shang Y. (2009). Videometrics: Principles and Research. Beijing China: Science Press.

  • [16] He Z. Wang B. (2003). Sub-pixel extraction algorithm using curve fitting method. Journal of Scientific Instrument 24 195-197.

  • [17] Chang S.-T. Sun Z.-Y. Zhang Y.-Y. Zhu W. (2014). Radiation measurement of small targets based on PSF. Optics and Precision Engineering 22 (11) 2879-2887.

  • [18] Duan Z.-Y. Wang N. Zhao W.-H. et al. (2016). Study on calibration method based on lattice calibration plate in vision measurement system. Acta Optica Sinica 36 (5) 0515004.

  • [19] Fei Z.-G Xu X.-J. Anthimos G. (2016). Short-arc measurement and fitting based on the bidirectional prediction of observed data. Measurement Science and Technology 27 (2) 025013.

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IMPACT FACTOR 2018: 1,122
5-year IMPACT FACTOR: 1,157



CiteScore 2018: 1.39

SCImago Journal Rank (SJR) 2018: 0.325
Source Normalized Impact per Paper (SNIP) 2018: 0.881

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