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Proceedings Paper

A method to auto-estimate edge detection direction
Author(s): Z. Yin; B. G. Liu; F. D. Chen; G. D. Liu; F. Wan
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Paper Abstract

In machine vision measurement, the edge is a key point for fitting geometric parameter. There are two problems in the edge detection process. First, there is redundant information for the object with complex shape in the field of the view. Second, the surface of the object is full of texture which is misidentified as the edge. The texture processes similar feature to the edge and cannot be removed by filter. To solve the above problems, vision sight is proposed to get an interesting region and remove redundant information. A new algorithm based on fuzzy entropy is used to auto-estimate the edge detection direction from the pure region to mixed region in order to avoid the textures which misidentified as the edge. Comparing the algorithm with Canny, the former gets less texture points than the latter. A mask film is used as a standard to weight the validity of the algorithm. The experimental result shows that the algorithm proposed by this paper is robust and accuracy in detecting edge.

Paper Details

Date Published: 31 January 2013
PDF: 8 pages
Proc. SPIE 8759, Eighth International Symposium on Precision Engineering Measurement and Instrumentation, 87590D (31 January 2013); doi: 10.1117/12.2015044
Show Author Affiliations
Z. Yin, Harbin Institute of Technology (China)
B. G. Liu, Harbin Institute of Technology (China)
F. D. Chen, Harbin Institute of Technology (China)
G. D. Liu, Harbin Institute of Technology (China)
F. Wan, Harbin Institute of Technology (China)

Published in SPIE Proceedings Vol. 8759:
Eighth International Symposium on Precision Engineering Measurement and Instrumentation
Jie Lin, Editor(s)

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