High-precision Measurement Method for Copper Plate Hole Size Based on Partial Area Effect

In the quality control of automated production, machine vision is one of the most important technologies in non-contact measurement of mold products. This paper will improve the sub-pixel edge extraction method based on partial area effect, which mainly improves two aspects: 1) enhancing the connectivity of edge segment and integrity of edge contour; 2)reducing the computational complexity of extracting target sub-pixel edges and improving detection speed. The improved method is used to measure the diameter of the circular hole of the copper plate. The experimental results show that the proposed improvement can effectively improve the accuracy of the detection of the size of the hole. The average relative accuracy is 0.16%, which is 47% higher than before improvement, and the average efficiency is 20% higher than before improvement.

[1]  Chung-Yen Su,et al.  Effective subpixel edge detection for LED probes , 2016, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[2]  Agustín Trujillo-Pino,et al.  Accurate subpixel edge location based on partial area effect , 2013, Image Vis. Comput..

[3]  Zhao Ai-ming Sub Pixel Edge Detection Algorithm Based on Guadrativ Curve Fitting , 2006 .

[4]  Frédéric Truchetet,et al.  Subpixel edge detection for dimensional control by artificial vision , 2001, J. Electronic Imaging.

[5]  Jie Jiang,et al.  Edge detection in planet image using an improved partial area effect algorithms , 2018, Other Conferences.

[6]  Shuen-De Wu,et al.  Sub-pixel edge detection of LED probes based on partial area effect , 2015, 2015 1st International Conference on Industrial Networks and Intelligent Systems (INISCom).

[7]  Owen Robert Mitchell,et al.  Edge Location to Subpixel Values in Digital Imagery , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[8]  Stephan Hussmann,et al.  A high-speed subpixel edge detector implementation inside a FPGA , 2003, Real Time Imaging.

[9]  Dandan Liu,et al.  Subpixel edge location based on orthogonal Fourier-Mellin moments , 2008, Image Vis. Comput..

[10]  Frédéric Bouchara,et al.  Sub-pixel Edge Fitting Using B-Spline , 2007, MIRAGE.

[11]  Sun Qiu-chen A Sub-pixel Edge Detection Method Based on Cubic Spline Interpolation , 2014 .

[12]  Sugata Ghosal,et al.  Orthogonal moment operators for subpixel edge detection , 1993, Pattern Recognit..

[13]  Tian Jun-wei Sub-pixel edge detection algorithm based on Gauss fitting , 2011 .