Abstract
Two neural network based vision subsystems for image recognition in micromechanics were developed. One subsystem is for shape recognition and another subsystem is for texture recognition. Information about shape and texture of the micro workpiece can be used to improve precision of both assembly and manufacturing processes. The proposed subsystems were tested off-line in two tasks. In the task of 3mm screw shape recognition the recognition rate of 92.5% was obtained for image database of screws manufactured with different positions of the cutters. In the task of texture recognition of mechanically treated metal surfaces the recognition rate of 99.8% was obtained for image database of four texture types corresponding to metal surfaces after milling, polishing with sandpaper, turning with lathe and polishing with file. We propose to combine these two subsystems to computer vision system for manufacturing of micro workpieces.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Baidyk, T., Kussul, E., Makeyev, O., Caballero, A., Ruiz, L., Carrera, G., Velasco, G.: Flat image recognition in the process of microdevice assembly. Pattern Recognition Letters Vol. 25 (1), pp. 107–118 (2004).
Kussul, E., Baidyk, T., Ruiz-Huerta, L., Caballero-Ruiz, A., Velasco, G., Kasatkina, L.: Development of micromachine tool prototypes for microfactories. Journal of Micromechanics and Microengineering Vol. 12, pp. 795–812 (2002).
Kussul, E., Rachkovskij, D., Baidyk, T., Talayev, S.: Micromechanical engineering: a basis of the low cost manufacturing of mechanical microdevices using microequipment. Journal of Micromechanics and Microengineering Vol. 6, pp. 410–425 (1996).
Kussul, E., Baidyk, T., Ruiz-Huerta, L., Caballero-Ruiz, A., Velasco, G.: Scaling down of microequipment parameters. Precision Engineering Vol. 30, pp. 211–222 (2006).
Okazaki, Yuichi, Kitahara, Tokio: Micro-lathe equipped with closed-loop numerical control. Proceedings of the 2-nd International Workshop on Microfactories, Switzerland, pp. 87–90 (2000).
Bleuler, H., Clavel, R., Breguet, J-M., Langen, H., Pernette, E.: Issues in precision motion control and microhandling. Proceedings of the IEEE International Conference on Robotics & Automation, San Francisco, pp. 959–964 (2000).
Jonathan Wu, Q.M., Ricky Lee, M.F., Clarence W. de Silva: Intellihgent 3-D sensing in automated manufacturing processes. Proceedings of the IEEE/ASME international conference on advanced intelligent mechatronics, Italy, pp. 366–370 (2001).
Lee, S.J., Kim, K., Kim, D.-H., Park, J.-O., Park, G.T.: Recognizing and tracking of 3-D-shaped micro parts using multiple visions for micromanipulation. Proceedings of the IEEE international symposium on micromechatronics and human science, Japan, pp. 203–210 (2001).
Kim, J.Y., Cho, H.S.: A vision based error-corrective algorithm for flexible parts assembly. Proceedings of the IEEE international symposium on assembly and task planning, Portugal, pp. 205–210 (1999).
Matti Pietikäinen, Tomi Nurmela, Topi Mäenpää, Markus Turtinen: View-based recognition of real-world textures. Pattern Recognition Vol. 37, pp. 313–323 (2004).
Grigorescu, C., Petkov, N.: Distance sets for shape filtres and shape recognition. IEEE Transactions on Image Processing Vol. 12 (10), pp. 1274–1286 (2003).
Kussul, E.M., Baidyk, T.N.: Permutative coding technique for handwritten digit recognition. Proceedings of the IEEE international joint conference on neural networks, Oregon, USA, pp. 2163–2168 (2003).
Kussul, E., Baidyk, T., Kussul, M.: Neural network system for face recognition. Proceedings of the IEEE international symposium on circuits and systems, Vancouver, Canada, pp. V-768–V-771 (2004).
Kussul, E., Baidyk, T., Wunsch, D., Makeyev, O., Martín, A.: Permutation coding technique for image recognition systems. IEEE Transactions on Neural Networks Vol. 17 (6), pp. 1566–1579 (2006).
Chi-ho Chan, Grantham K.H. Pang: Fabric defect detection by Fourier analysis, IEEE Transactions on Industry Applications Vol. 36 (5), pp. 1267–1276 (2000).
Hepplewhite, L., Stonham, T.J.: Surface inspection using texture recognition, Proceedings of the 12th IAPR international conference on pattern recognition, Israel, pp. 589–591 (1994).
Sanchez-Yanez, R., Kurmyshev, E., Fernandez, A.: One-class texture classifier in the CCR feature space, Pattern Recognition Letters Vol. 24, pp. 1503–1511 (2003).
Brenner, D., Principe, J.C., Doty, K.L.: Neural network classification of metal surface properties using a dynamic touch sensor. Proceedings of the international joint conference on neural networks, Seattle, pp. 189–194 (1991)
Rosenblatt, F.: Principles of neurodynamics. Spartan books, New York (1962).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag London Limited
About this paper
Cite this paper
Baidyk, T., Kussul, E., Makeyev, O. (2009). Computer Vision System for Manufacturing of Micro Workpieces. In: Allen, T., Ellis, R., Petridis, M. (eds) Applications and Innovations in Intelligent Systems XVI. SGAI 2008. Springer, London. https://doi.org/10.1007/978-1-84882-215-3_2
Download citation
DOI: https://doi.org/10.1007/978-1-84882-215-3_2
Publisher Name: Springer, London
Print ISBN: 978-1-84882-214-6
Online ISBN: 978-1-84882-215-3
eBook Packages: Computer ScienceComputer Science (R0)