Achieving the Measurement of Tool Diameter by the Boundary Tracing Algorithm Based on Model

Yue Shen Lai; Meng Shi; Jun Wei Tian; Gang Cheng

doi:10.4028/www.scientific.net/AMR.411.469

Paper Titles

Design of Silicon Based on Bio-Electrodes for Deep Brain Stimulation
p.447

Ballistic Characteristics of Non-Silicon MEMS Inertial Trigger Switch
p.452

Failure Analysis and Design Improvements of MEMS Explosive Interrupter
p.456

Simulation and Analysis of Measurement Method for Projectile Axial Acceleration by MEMS Sensor
p.461

Achieving the Measurement of Tool Diameter by the Boundary Tracing Algorithm Based on Model
p.469

Fabrication of Fine-Line Pattern with Image Reversal Process
p.474

Research on the Tool Images Evaluation Based on Auto-Focus Technology
p.478

A Rapid Separation Method for Nonuniform Image Segmentation
p.483

Design of High Speed and Parallel Compression System Used in the Big Area CCD of High Frame Frequency
p.488

HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 411Achieving the Measurement of Tool Diameter by the...

Achieving the Measurement of Tool Diameter by the Boundary Tracing Algorithm Based on Model

Abstract:

Boundary tracing method is an important preprocessing instrument for image recognition and image measurement, but the traditional boundary tracing method exits a conflict between the veracity and the speed. In response to these problems, we propose the boundary tracking algorithm based on the model, and then obtain the tool diameter. Experiments show that the boundary tracking algorithm can achieve a good boundary track. Compared two algorithms of diameter measurements, we obtain that the least square method runs shorter, and more efficient.

You might also be interested in these eBooks

Precision Engineering and Non-Traditional Machining

View Preview

Info:

Periodical:

Advanced Materials Research (Volume 411)

Pages:

469-473

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.411.469

Citation:

Cite this paper

Online since:

November 2011

Authors:

Yue Shen Lai, Meng Shi, Jun Wei Tian, Gang Cheng

Keywords:

Arc Fitting, Boundary Tracing, Image Processing, Least-Square Method (LSM)

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Zhong Zhiguang, Lu Jun, Liu Weirong, Visual C++. Net Case and Analysis of Digital Image Processing, Bei Jing: Tsinghua University Press, (2003).

Google Scholar

[2] Wang Yukun, Wei Guojun, Improment of Boundary Tracking Algorithm for Image Analysis, China Rubber Industry. 9 (2008) 554-556.

Google Scholar

[3] Cui Fengkui, Zhang Fengshou, Bai Lu, Using Neighborhood Points to Trace Edge of Object, Journal of Luoyang Institute of Technology. 22 (2001) 28-34.

Google Scholar

[4] Zhang Hongtao, Duan Fajie, Ye Shenghua, Study on a Fast Method for Sub-pixel Edge Detection, Acta Metrologica Sinica. 23 (2002) 263-265, 270.

Google Scholar

[5] Sun Chaoming, Fu Degui, Curve Fitting Algorithm of Different Geometry, Advance Manufacture Technique. 25 (2006) 25-27.

Google Scholar

[6] Nie Xiang, Zhang Ruilin, How to Realize of Minimum Square Estimation in Curve-fitting, Journal of Shaanxi University of Technology. 3 (2000) 79-82.

Google Scholar

[7] Hou Qian, Wang Bing, Jia Qiang, The Application of Curve Fitting Algorithm in Arc Detection, Coal Engineering. 6 (2008) 88-90.

Google Scholar