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Nurbs-Based Profile Reconstruction using Constrained Fitting Techniques

  • B. M. Imani (a1) and S. A. Hashemian (a1)
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.

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*Corresponding author (imani@um.ac.ir)
References
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1. Várady, T., Martin, R. R. and Cox, J., “Reverse Engineering of Geometric Models—n Introduction,” Computer-Aided Design, 29, pp. 255268 (1997).
2. Porrill, J., “Optimal Combination and Constraints for Geometrical Sensor Data,” The International Journal of Robotics Research, 7, pp. 6677 (1988).
3. Werghi, N., Fisher, R., Robertson, C. and Ashbrook, A., “Object Reconstruction by Incorporating Geometric Constraints in Reverse Engineering,” Computer-Aided Design, 31, pp. 363399 (1999).
4. Benkő, P., Kós, G., Várady, T., Andor, L. and Martin, R. R., “Constrained Fitting in Reverse Engineering,” Computer Aided Geometric Design, 19, pp. 173205 (2002).
5. Ke, Y., Zhu, W., Liu, F. and Shi, X., “Constrained Fitting for 2D Profile-Based Reverse Modeling,” Computer-Aided Design, 38, pp. 101114 (2006).
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. 1115 (1972).
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).
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).
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).
10. Borges, G. A. and Aldon, M.-J., “Line Extraction in 2D Range Images for Mobile Robotics,” Journal of Intelligent & Robotic Systems, 40, pp. 267297 (2004).
11. Ke, Y., Fan, S., Zhu, W., Li, A., Liu, F. and Shi, X., “Feature-Based Reverse Modeling Strategies,” Computer-Aided Design, 38, pp. 485506 (2006).
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).
13. Piegl, L. and Tiller, W., The NURBS Book, 2nd Ed., Springer-Verlag, New York, NY (1997).
14. Fisher, J., Lowther, J. and Shene, C.-K., “If You Know B-Splines Well, You Also Know NURBS!,” ACM SIGCSE Bulletin, 36, pp. 343347 (2004).
15. Piegl, L. A. and Tiller, W., “Biarc Approximation of NURBS Curves,” Computer-Aided Design, 34, pp. 807814 (2002).
16. Optimization Toolbox, http://www.mathworks.com, The Mathworks Inc (2010).
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Journal of Mechanics
  • ISSN: 1727-7191
  • EISSN: 1811-8216
  • URL: /core/journals/journal-of-mechanics
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