Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-11T09:27:41.143Z Has data issue: false hasContentIssue false
  • English
  • Français

Nurbs-Based Profile Reconstruction using Constrained Fitting Techniques

Published online by Cambridge University Press:  09 August 2012

B. M. Imani  and
S. A. Hashemian
B. M. Imani*
Affiliation:
Department of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
S. A. Hashemian
Affiliation:
Department of Mechanical Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
*
*Corresponding author (imani@um.ac.ir)
Get access

Abstract

Ordered data point cloud obtained by laser-scanning, image processing or contact digitizing techniques is widely used for reconstructing a cross section profile in the field of reverse engineering. In this research, a comprehensive algorithm for reconstruction of 2D profile is developed based on NURBS parametric curve theory. In this regard, the line, arc and B-spline segments are firstly extracted from the set of ordered data points using a developed segment detection algorithm. Then, the final profile is reconstructed using the newly proposed algorithm of constrained local fitting which approximates these segments by NURBS curves with appropriate geometric continuity conditions. The validity, capability and functionality of the developed method are investigated by some practical case studies. Results show that developed algorithm can be integrated and improve the functionality of exiting reverse engineering systems.

Keywords

NURBS curvesReverse engineeringConstrained local fitting
Type
Articles
Information
Journal of Mechanics , Volume 28 , Issue 3 , September 2012 , pp. 407 - 412
Copyright
Copyright © The Society of Theoretical and Applied Mechanics, R.O.C. 2012

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

1. Várady, T., Martin, R. R. and Cox, J., “Reverse Engineering of Geometric Models—n Introduction,” Computer-Aided Design, 29, pp. 255–268 (1997).CrossRefGoogle Scholar
2. Porrill, J., “Optimal Combination and Constraints for Geometrical Sensor Data,” The International Journal of Robotics Research, 7, pp. 66–77 (1988).CrossRefGoogle Scholar
3. Werghi, N., Fisher, R., Robertson, C. and Ashbrook, A., “Object Reconstruction by Incorporating Geometric Constraints in Reverse Engineering,” Computer-Aided Design, 31, pp. 363–399 (1999).CrossRefGoogle Scholar
4. Benkő, P., Kós, G., Várady, T., Andor, L. and Martin, R. R., “Constrained Fitting in Reverse Engineering,” Computer Aided Geometric Design, 19, pp. 173–205 (2002).CrossRefGoogle Scholar
5. Ke, Y., Zhu, W., Liu, F. and Shi, X., “Constrained Fitting for 2D Profile-Based Reverse Modeling,” Computer-Aided Design, 38, pp. 101–114 (2006).CrossRefGoogle Scholar
6. Duda, R. O. and Hart, P. E., “Use of the Hough Trans-Formation to Detect Lines and Curves in Pictures,” Communications of the ACM, 15, pp. 11–15 (1972).CrossRefGoogle Scholar
7. Song, Z., Chen, Y. Q., Ma, L. L. and Chung, Y. C., “Some Sensing and Perception Techniques for an Omnidirectional Ground Vehicle with a Laser Scan-Ner,” Proceedings of IEEE International Symposium on Intelligent Control (2002).Google Scholar
8. Sen, Z., Adams, M., Fan, T. and Xie, L. H., “Geometrical Feature Extraction Using 2D Range Scanner,” Proceedings of 4th International Conference on Control and Automation, ICCA ′03 (2003).Google Scholar
9. Castro, D., Nunes, U. and Ruano, A., “Feature Extraction and for Moving Objects Tracking System in Indoor Environments,” Proceedings of 5th IFAC/EURON Symposium on Intelligent Autonomous Vehicles, IAV'04 (2004).Google Scholar
10. Borges, G. A. and Aldon, M.-J., “Line Extraction in 2D Range Images for Mobile Robotics,” Journal of Intelligent & Robotic Systems, 40, pp. 267–297 (2004).CrossRefGoogle Scholar
11. Ke, Y., Fan, S., Zhu, W., Li, A., Liu, F. and Shi, X., “Feature-Based Reverse Modeling Strategies,” Computer-Aided Design, 38, pp. 485–506 (2006).CrossRefGoogle Scholar
12. Xavier, J., Pacheco, M., Castro, D., Ruano, A. and Nunes, U., “Fast Line, Arc/Circle and Leg Detection from Laser Scan Data in a Player Driver,” Proceedings of IEEE International Conference on Robotics and Automation, ICRA 2005 (2005).Google Scholar
13. Piegl, L. and Tiller, W., The NURBS Book, 2nd Ed., Springer-Verlag, New York, NY (1997).CrossRefGoogle Scholar
14. Fisher, J., Lowther, J. and Shene, C.-K., “If You Know B-Splines Well, You Also Know NURBS!,” ACM SIGCSE Bulletin, 36, pp. 343–347 (2004).CrossRefGoogle Scholar
15. Piegl, L. A. and Tiller, W., “Biarc Approximation of NURBS Curves,” Computer-Aided Design, 34, pp. 807–814 (2002).CrossRefGoogle Scholar
16. Optimization Toolbox, http://www.mathworks.com, The Mathworks Inc (2010).Google Scholar