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Proceedings Paper

An improved dynamic double threshold Canny edge detection algorithm
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Paper Abstract

With the upgrade of the industry, robots urgently need to track moving targets at high speed. Therefore, the detection algorithms in machine vision technology need to be improved. Aiming at the problem that high and low thresholds need to be fixed in traditional Canny edge detection algorithm, an improved dynamic double threshold Canny algorithm is proposed. Constantly increasing the size of the threshold, Using the size of the area where the image edge is closed as a standard, finally to determine the best threshold, In order to achieve the best detection effect. Experimental results show that, Improved dynamic double threshold Canny algorithm not only improves the edge detection effect by 9% on average compared with the traditional algorithm, but also detects more complete image information and has stronger adaptability.

Paper Details

Date Published: 14 February 2020
PDF: 8 pages
Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 1143016 (14 February 2020); doi: 10.1117/12.2539300
Show Author Affiliations
Zhikang Xiao, Wuhan Institute of Technology (China)
Yang Zou, Wuhan Institute of Technology (China)
Zhen Wang, Wuhan Institute of Technology (China)

Published in SPIE Proceedings Vol. 11430:
MIPPR 2019: Pattern Recognition and Computer Vision
Nong Sang; Jayaram K. Udupa; Yuehuan Wang; Zhenbing Liu, Editor(s)

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