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Research on target location method based on varistor image
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Paper Abstract

In order to more accurately locate and segment the varistor image to achieve the varistor image data set necessary for automatic construction of deep learning. This paper proposes a method for locating and stitching the body and stitch of varistor based on Hough transform and mathematical morphology. In order to obtain an image that eliminates surface reflection, the method first acquires a varistor image through a coaxial light source. Secondly, performing preprocessing on the image based on denoising, graying, and binarization; then, using the Hough transform based on circle detection to locate the body of the resistor; further separating the body and the stitches, firstly performing edge searching on the positioned body portion, and then performing background filling on the inside of the body, and finally using a mathematical morphology etching operation to eliminate the edge marks of the body to obtain the positioning of the stitches. The experiment aimed to locate and segment 91 varistor samples, and use the effective and correct data indicators to evaluate the segmentation results. The experimental results show that the actual results of the proposed method are ideal and have a good target segmentation effect, which is beneficial to provide reliable varistor image data sets necessary for deep learning.

Paper Details

Date Published: 18 December 2019
PDF: 7 pages
Proc. SPIE 11342, AOPC 2019: AI in Optics and Photonics, 113420E (18 December 2019); doi: 10.1117/12.2546948
Show Author Affiliations
Bo Gong, Guilin Univ. of Technology (China)
Lei Xiao, Guilin Univ. of Technology (China)
Chunchun Li, Guilin Univ. of Technology (China)
Tiejun Yang, Guilin Univ. of Technology (China)


Published in SPIE Proceedings Vol. 11342:
AOPC 2019: AI in Optics and Photonics
John Greivenkamp; Jun Tanida; Yadong Jiang; HaiMei Gong; Jin Lu; Dong Liu, Editor(s)

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