Self-adaptive method to distinguish inner and outer contours of industrial computed tomography image for rapid prototype

Duan Liming; Ye Yong; Zhang Xia; Zuo Jian

Volume 25 Issue 04

Mar. 2013

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Article Navigation > High Power Laser and Particle Beams > 2013 > 25(04): 1017-1020

sheng yong1, jiang gang, zhu zheng-he, et al. Dielectronicrecombination rate study of Hlike， Helike and Lilike Mg and Al ions[J]. High Power Laser and Particle Beams, 2002, 14.

Citation:

Duan Liming, Ye Yong, Zhang Xia, et al. Self-adaptive method to distinguish inner and outer contours of industrial computed tomography image for rapid prototype[J]. High Power Laser and Particle Beams, 2013, 25: 1017-1020.

sheng yong1, jiang gang, zhu zheng-he, et al. Dielectronicrecombination rate study of Hlike， Helike and Lilike Mg and Al ions[J]. High Power Laser and Particle Beams, 2002, 14.

Citation:

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Self-adaptive method to distinguish inner and outer contours of industrial computed tomography image for rapid prototype

Duan Liming^{1
,
,},
Ye Yong^1,2,
Zhang Xia^1,2,
Zuo Jian^1,2

1.
ICT Research Center,Chongqing University,Chongqing 400044,China;
2.
College of Mechanical Engineering,Chongqing University,Chongqing 400044,China

Received Date: 2012-09-07
Rev Recd Date: 2012-11-16
Publish Date: 2013-03-09

Abstract

Abstract

A self-adaptive identification method is proposed for realizing more accurate and efficient judgment about the inner and outer contours of industrial computed tomography (CT) slice images. The convexity-concavity of the single-pixel-wide closed contour is identified with angle method at first. Then, contours with concave vertices are distinguished to be inner or outer contours with ray method, and contours without concave vertices are distinguished with extreme coordinate value method. The method was chosen to automatically distinguish contours by means of identifying the convexity and concavity of the contours. Thus, the disadvantages of single distinguishing methods, such as ray methods time-consuming and extreme coordinate methods fallibility, can be avoided. The experiments prove the adaptability, efficiency, and accuracy of the self-adaptive method.
- inner and outer contour distinguishing,
- ray method,
- extreme coordinate value method,
- self-adaptive,
- industrial computed tomography

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