Machine Vision Detection on Circle with Non-Uniform Points

Qing Min Liu; Xue Li

doi:10.4028/www.scientific.net/AMM.687-691.819

Paper Titles

The Research on Real-Time Position Monitoring System in Slurry Pipeline Grading Transmission
p.802

An Exploration of Fall-Down Detection by Smart Wristband
p.805

Risk Assessment and Risk Warning for Current Transformer Automatic Verification System
p.809

The Quality Assurance and Online Diagnosis Technology of Automatic Verification System for Transformer
p.815

Machine Vision Detection on Circle with Non-Uniform Points
p.819

The Design and Application of the Intelligent Vehicle Inspection System Based on RFID
p.823

The New Structure Pedestrian Detection Based on the FPGA
p.827

The Wireless Sensor Networks Applied in the Coal Mine Safety Intelligent Monitoring System
p.832

Research on Facial Features of Major Chinese Nationalities
p.837

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 687-691Machine Vision Detection on Circle with...

Machine Vision Detection on Circle with Non-Uniform Points

Abstract:

s.The least-squares algorithm is usually used to fit data in circle detection. The application of the conventional least-squares algorithm is limited, its’ roundness error is bigger, and precision is lower. For detecting circle with data points of non-uniform distribution, developed an analysis algorithm for assessing the minimum zone roundness error. Center and radius can be accurately solved, without iteration, without truncation error. Visual measurements have been carried out for known diameter D=2.564mm tooth shape chain board’s aperture using the proposed methods, calculated results (Table 1) using four kinds of roundness error evaluation methods. Tooth shape chain board’s aperture diameter errors are 0.0157mm、0.0126mm、0.0117 mm and 0.0218mm, roundness errors are 0.0251 mm、0.0225mm、0.0228mm and 0.0244mm respectively. The minimum zone algorithm are suitable for distributed data of all kinds situation, particularly suitable for the realization of machine vision inspection system, fast speed for high precision, wide range of application.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 687-691)

Pages:

819-822

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.687-691.819

Citation:

Cite this paper

Online since:

November 2014

Authors:

Qing Min Liu*, Xue Li

Keywords:

Circle Detection, Image Processing, Machine Vision, Roundness Error

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] L.X. Cao, B.J. Wang: Roundness Detection Technology(National Defence Industry Press, Beijing 1998).

Google Scholar

[2] X. R Zhuo, H. W Liu: Study on the Relationship of Results of Four Kinds of Roundness Error Assessment Methods. Journal of Beijing University of Technology, Vol. 22(1996), p.111~114.

Google Scholar

[3] L. Wang, J. B Tan, J. Z Hang: Analyzing Rotation Error of Large-scale Gas Spindle Based on Roundness Evaluation. Infrared and Laser Engineering, Vol. 38(2009), p.441~444.

Google Scholar

[4] M.L. Sun: Evaluating Algorithm of Roundness Error Based on the Minimum Circumscribed Circle. Xi'an Aero technical College, Vol. 44(2010), p.109~111.

Google Scholar

[5] L. Xu, E. Oja, P. Kultanen: A New Curve Detection Method: Randomized Hough Transform (RHT). Pattern Recognition Letters, Vol. 11(1990), p.331~338.

DOI: 10.1016/0167-8655(90)90042-z

Google Scholar

[6] X.M. Li, Z. Y Shi: Development and Application of Convex Hull in the Assessment of Roundness Error. Machine Tools & Manufacture. Vol. 48(2006), p.135~139.

DOI: 10.1016/j.ijmachtools.2007.07.003

Google Scholar