Artículos

Pattern Recognition for Micro Workpieces Manufacturing

Reconocimiento de Patrones para la Fabricación de Microobjetos

Tatiana Baidyk¹, Ernst Kussul¹, Oleksandr Makeyev² and Graciela Velasco¹

¹ Center of Applied Science and Technological Development, National Autonomous University of Mexico (UNAM), tbaidyk@servidor.unam.mx , ekussul@servidor.unam.mx , graciela.velasco@ccadet.unam.mx.

² Department of Electrical and Computer Engineering, Clarkson University, USA, mckehev@hotmail.com.

Article received on June 13, 2008
Accepted on April 3, 2009

Abstract

Two neural classifiers were developed for image recognition: PCNC (Permutation Coding Neural Classifier) and LIRA (Limited Receptive Area) neural classifiers. These neural classifiers are multipurpose neural classifiers. We applied them in micromechanics. Information about shape and texture of the micro workpiece can be used to improve precision of both assembly and manufacturing processes. The proposed neural classifiers were tested offline in the both tasks.

Keywords: Computer vision, neural network, shape recognition, texture recognition, micromechanics.

Resumen

Dos clasificadores neuronales fueron desarrollados para el reconocimiento de imágenes: PCNC (clasificador neuronal con codificación con permutaciones) y LIRA (clasificador neuronal con área de recepción limitada). Estos clasificadores neuronales son clasificadores de diferentes aplicaciones. Nosotros usamos ellos en micromecánica. La información sobre la forma y textura del micro objeto se puede utilizar para mejorar la precisión de los procesos de ensamble y de fabricación. Los redes neuronales propuestos fueron probados fuera de línea en ambos tareas.

Palabras clave: Visión computacional, redes neuronales, reconocimiento de forma, reconocimiento de textura, micromecánica.

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Acknowledgment

This work was supported in part by projects CONACYT 50231, PAPIIT IN108606–3, PAPIIT IN116306–3.

References

1. Baidyk, T., Kussul, E., Makeyev, O. (2008) "Computer Vision Systems for Manufacturing of Micro Workpieces", The twenty–eight SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, Cambridge, UK, December 9–11, pp.14.        [ Links ]

2. Baidyk, T., Kussul, E., Makeyev, O., Caballero, A., Ruiz, L., Carrera, G., Velasco, G. (2004) "Flat image recognition in the process of microdevice assembly", Pattern Recognition Letters, Vol.25/1, pp. 107–118,.        [ Links ]

3. Baidyk, T., Kussul', E. (1999), Application of Genetic Algorithms to Optimization of Neuronet Recognition devices. Cybernetics and System Analysis. V.35, No 5, pp. 700–707.        [ Links ]

4. Bleuler, H., Clavel, R., Breguet, J–M., Langen, H., Pernette, E. (2000) "Issues in Precision Motion Control and Microhandling", Proc of the IEEE International Conference On Robotics & Automation, San Francisco, pp. 959–964.        [ Links ]

5. Brenner, D., Principe, J.C., Doty, K.L. (1991) "Neural network classification of metal surface properties using a dynamic touch sensor", Proc. Of the International Joint Conference on Neural Networks IJCNN'91, IEEE, Seattle, , Vol. 1, pp. 189–194.        [ Links ]

6. Chi–ho Chan and Grantham K.H. Pang, (2000) "Fabric defect detection by Fourier analysis", IEEE Transactions on Industry Applications, Vol. 36/5, pp. 1267–1276.        [ Links ]

7. Grigorescu, C. and Petkov, N. (2003) "Distance Sets for Shape Filtres and Shape Recognition", IEEE Trans, on Image Processing, Vol.12, N.10, pp. 1274–1286.        [ Links ]

8. Hepplewhite, L. and Stonham, T.J. (1994) "Surface inspection using texture recognition", Proc. of the 12^th IAPR International Conference on Pattern Recognition, Vol.1, pp. 589–591.        [ Links ]

9. Kim, J. Y. and Cho, H. S. (1999) "A Vision Based Error–Corrective Algorithm for Flexible Parts Assembly", Proc. of the IEEE International Symposium on Assembly and Task Planning, Portugal, 205–210.        [ Links ]

10. Kussul, E. and Baidyk, T. (2003) "Permutative coding technique for handwritten digit recognition", Proc. of the IEEE International Joint Conference on Neural Networks (IJCNN'2003), Portland, Oregon, USA, V.3, pp. 2163–2168, July 20–24.        [ Links ]

11. Kussul, E., Baidyk, T. and Kussul, M. (2004) "Neural Network System for Face Recognition", Proc. of the IEEE Internatrional Symposium on Circuits and Systems, ISCAS 2004, Vancouver, Canada, Vol.V, pp.V–768–V–771.        [ Links ]

12. Kussul, E., Baidyk, T., Ruiz–Huerta, L., Caballero–Ruiz, A., Velasco, G. (2006) "Scaling down of microequipment parameters", Precision Engineering, V30, pp.211–222.        [ Links ]

13. Kussul, E., Baidyk, T., Ruiz–Huerta, L., Caballero, A., Velasco, G., Kasatkina, L. (2002) "Development of Micromachine Tool Prototypes for Microfactories", Journal of Micromechanics and Microengineering, Vol. 12, 795–812.        [ Links ]

14. Kussul, E., Baidyk, T., Wunsch, D., Makeyev, O., Martín, A., (2006) "Permutation coding technique for image recognition systems", IEEE Trans. on Neural Networks, Vol. 17/6, pp. 1566–1579.        [ Links ]

15. Kussul, E., Rachkovskij, D., Baidyk, T., Talayev, S. (1996) "Micromechanical engineering: a basis of the low cost manufacturing of mechanical microdevices using microequipment", Journal of Micromechanics and Microengineering, 6, pp. 410–425.        [ Links ]

16. Lee, S. J., Kim, K., Kim, D.–H., Park, J.–O., Park, G.T. (2001) "Recognizing and Tracking of 3–D–Shaped Micro Parts Using Multiple Visions for Micromanipulation", Proc. of the IEEE International Symposium on Micromechatronics and Human Science, pp. 203–210.        [ Links ]

17. Makeyev, O., Sazonov, E., Baidyk, T., Martin, A. (2008). "Limited receptive area neural classifier for texture recognition of mechanically treated metal surfaces", Neurocomputing, Issue 7–9, Vol. 71, pp. 1413–1421.        [ Links ]

18. Martin, A., Baidyk, T. (2006). "Neural classifier for micro screw shape recognition in micromechanics", CLEI 2006, IFIP WCC AI2006, Santiago de Chile, Chile, pp. 10        [ Links ]

19. Okazaki, Yu. and Kitahara, T. (2000) "Micro–Lathe Equipped with Closed–Loop Numerical Control", Proc.of the 2–nd International Workshop on Microfactories, Switzerland, pp. 87– 90.        [ Links ]

20. Pietikäinen, M., Nurmela, T., Mäenpää T., Turtinen, M. (2004). "View–based recognition of real–world textures", Pattern Recognition, Vol. 37, pp. 313–323.        [ Links ]

21. Rosenblatt, F. (1962). Principles of neurodynamics, Spartan books, New York.        [ Links ]

22. Sanchez–Yanez, R., Kurmyshev, E., Fernandez, A. (2003) "One–class texture classifier in the CCR feature space", Pattern Recognition Letters, Vol. 24, pp. 1503–1511.        [ Links ]

23. Toledo, G., Kussul, E., Baidyk, T. (2004) "Neural classifier LIRA for recognition of micro work pieces and their positions in the processes of microassembly and micromanufacturing". Proceedings of the 7 All–Ukrainian International conference, 11–15 October 2004, Kiev, Ukraine, p. 17–20        [ Links ]

24. Toledo–Ramírez, G., Kussul, E., Baidyk, T. (2006), "Neural classifier for micro work pieces recognition", Image and Vision Computing, Vol. 24, Issue 8, pp.827–836        [ Links ]

25. Vapnik, V. (1995) The Nature of Statistical Learning Theory, Springer–Verlag, p. 188.        [ Links ]

26. Vapnik, V., Kotz, S. (2006) Estimation of Dependences Based on Empirical Data, Springer, p. 510.        [ Links ]

27. Wu, J. Q. M., Lee, M. F. R., Cl. W. de Silva, (2001) "Intelligent 3–D Sensing in Automated Manufacturing Processes", Proc. of the IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Italy, pp. 366–370.        [ Links ]