Study on Algorithms of Graphic Element Recognition for Precise Vectorization of Industrial Computed Tomographic Image

Article ID

H752M

Study on Algorithms of Graphic Element Recognition for Precise Vectorization of Industrial Computed Tomographic Image

Dr. Fenglin Liu
Dr. Fenglin Liu
Bing He
Bing He Chongqing University, Chongqing
Bi Bi1
Bi Bi1
DOI

Abstract

Circle, line and circular arc are the common basic graphic elements in industrial computed tomography (ICT) image. The algorithm of recognizing such elements is the key to industrial CT image precise vectorization. An industrial CT image vectorization system has been studied, including different recognition methods for these elements. Firstly, based on facet model, the sub-pixel edge of an industrial CT image is extracted. Then, the circles are recognized by an improved algorithm based on probability of existence map, while the lines are recognized with the set intersection algorithm of fitting a straight line, and the circular arcs are recognized by the combination of the perpendicular bisector tracing algorithm and least squares function. Finally, the graphic element parameters are measured according to recognition results, and the drawing exchange file (DXF) is produced and transmitted into the computer aided design (CAD) system to be edited and consummated. The experimental results show that these methods are capable of recognizing graphic elements in industrial CT image with an excellent accuracy, besides, the absolute errors of circles are less than 0.1 mm, and the relative errors are less than 0.5%. It can satisfy the industrial CT vectorization requirements of higher precision, rapid speed and non-contact.

Study on Algorithms of Graphic Element Recognition for Precise Vectorization of Industrial Computed Tomographic Image

Circle, line and circular arc are the common basic graphic elements in industrial computed tomography (ICT) image. The algorithm of recognizing such elements is the key to industrial CT image precise vectorization. An industrial CT image vectorization system has been studied, including different recognition methods for these elements. Firstly, based on facet model, the sub-pixel edge of an industrial CT image is extracted. Then, the circles are recognized by an improved algorithm based on probability of existence map, while the lines are recognized with the set intersection algorithm of fitting a straight line, and the circular arcs are recognized by the combination of the perpendicular bisector tracing algorithm and least squares function. Finally, the graphic element parameters are measured according to recognition results, and the drawing exchange file (DXF) is produced and transmitted into the computer aided design (CAD) system to be edited and consummated. The experimental results show that these methods are capable of recognizing graphic elements in industrial CT image with an excellent accuracy, besides, the absolute errors of circles are less than 0.1 mm, and the relative errors are less than 0.5%. It can satisfy the industrial CT vectorization requirements of higher precision, rapid speed and non-contact.

Dr. Fenglin Liu
Dr. Fenglin Liu
Bing He
Bing He Chongqing University, Chongqing
Bi Bi1
Bi Bi1

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Bing He. 2011. “. Global Journal of Research in Engineering – A : Mechanical & Mechanics GJRE-A Volume 11 (GJRE Volume 11 Issue A5): .

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Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

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Study on Algorithms of Graphic Element Recognition for Precise Vectorization of Industrial Computed Tomographic Image

Dr. Fenglin Liu
Dr. Fenglin Liu
Bing He
Bing He Chongqing University, Chongqing
Bi Bi1
Bi Bi1

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