Flat image recognition in the process of microdevice assembly

Pattern Recognition Letters

Volumn 25, Issue 1, 2004, Pages 107-118

  Baidyk, T ^a   Kussul, E ^a   Makeyev, O ^b   Caballero, A ^a   Ruiz, L ^a   Carrera, G ^a   Velasco, G ^a  

^a UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO   (Mexico)

^b TARAS SHEVCHENKO NATIONAL UNIVERSITY OF KYIV   (Ukraine)

Author keywords

Image recognition; Microassembly; Neural classifier; Neural interpolator

Indexed keywords

ASSEMBLY; IMAGE PROCESSING;

IMAGE RECOGNITION; MICRODEVICES;

PATTERN RECOGNITION;

PATTERN RECOGNITION;

EID: 0344551945     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2003.09.005     Document Type: Article

References (36)

1. Baidyk, T.N., 2001a. Application of flat image recognition technique for automation of micro device production. In: Proc. 2001 IEEE/ASME Internat. Conf. on Advanced Intelligent Mechatronics, Teatro Sociale Como, Italy, pp. 488-494
2. Baidyk, T.N., 2001b. La Aplicación de los Métodos del Reconocimiento de las Imágenes Planas para la Automatización de la Producción de Micro Dispositivos. In: Congreso "SOMI-XYI", Queretero, México, p. 12
3. Baidyk, T.N., Kussul, E.M., 2002. Application of neural classifier for flat image recognition in the process of microdevice assembly. In: Proc. IEEE Internat. Joint Conf. on Neural Networks, Hawaii, USA, vol. 1, pp. 160-164
4. Belongie, S., Malik, J., Puzicha, J., 2001. Matching shapes. In: Proc. Eighth IEEE Internat. Conf. on Computer Vision ICCV, vol. 1, pp. 454-461
5. Belongie S. Malik J. Puzicha J. Shape matching and object recognition using shape contexts IEEE Trans. Pattern Anal. Machine Intell. 24 4 2002 509-522
6. Bleuler, H., Clavel, R., Brequet, J.-M., Langen, H., Pernette, E., 2000. Issues in precision motion control and microhandling. In: Proc. 2000 IEEE Internat. Conf. on Robotics and Automation, USA, pp. 959-964
7. Bottou, L., Cortes, C., Denker, J., Drucker, H., Guyon, L., Jackel, L., LeCun, J., Muller, U., Sackinger, E., Simard, P., Vapnik, V., 1994. Comparison of classifier methods: A case study in handwritten digit recognition. In: Proc. 12th IAPR Internat. Conf. on Pattern Recognition, vol. 2, pp. 77-82
8. Burel, G., Bernard, F., Venema, W.J., 1995. Vision feedback for SMD placement using neural networks. In: IEEE Internat. Conf. on Robotics and Automation, pp. 1491-1496
9. Cheng-Kin K., Nakashima, K., Saco, H., Fujisawa, H., 2002. Handwritten digit recognition using state-of-the-art techniques. In: Proc. IEEE Eighth Internat. Workshop on Frontiers in Handwritten Recognition, Ontario, Canada, pp. 320-325
10. Clarke T.J.W. Prager R.W. Fallside F. The modified Kanerva model: Theory and results for real-time word recognition IEEE Proc. Radar Signal Process. 138 1 1991 25-31
11. Duda R. Hart P. Pattern Classification and Scene Analysis 1973 Wiley-Interscience Publisher New York
12. Eddy D.S. Sparks D.R. Application of MEMS technology in automotive sensors and actuators Proc. IEEE 86 8 1998 1747-1755
13. Fatikow, S., Rembold, U., 1996. An automated microrobot-based desktop station for micro assembly and handling of microobjects. In: Proc. IEEE Conf. on Emerging Technologies and Factory Automation, vol. 2, pp. 586-592
14. Friedrich C.R. Vasile M.J. Development of the micromilling process for high-aspect-ratio micro structures J. Microelectromech. Systems 5 1996 33-38
15. Howlett, B., Jain, J.C. (Eds.), 2000. Radial Basis Function Networks
16. Jonathan Wu Q.M., Ricky Lee, M.F., de Silva, C.W., 2001. Intelligent 3-D sensing in automated manufacturing processes. In: Proc. IEEE/ASME Internat. Conf. on Advanced Intelligent Mechatronics, Italy, pp. 366-370
17. Kim, J.Y., Cho, H.S., 1999a. A vision based error-corrective algorithm for flexible parts assembly. In: Proc. IEEE Internat. Symposium on Assembly and Task Planning, Portugal, pp. 205-210
18. Kim, J.Y., Cho, H.S., 1999b. Visual sensor-based measurement for deformable peg-in-hole tasks. In: Proc. IEEE/RSJ Internat. Conf. on Intelligent Robots and Systems, pp. 567-572
19. Kussul, E., Baidyk, T., 1994. Neural random threshold classifier in OCR application. In: Proc. Second All-Ukrainian Internat. Conf., Kiev, Ukraine, pp. 154-157
20. Kussul, E., Baidyk, T., 2002. Improved method of handwritten digit recognition tested on MNIST database. In: 15-th Internat. Conf. on Vision Interface, Calgary, Canada, pp. 192-197
21. Kussul E. Baidyk T. Lukovitch V. Rachkovskij D. Adaptive high performance classifier based on random threshold neurons Trappl R. Cybernetics and Systems'94 1994 1687-1695 World Scientific Publishing Co. Pte. Ltd. Singapore
22. Kussul E.M. Rachkovskij D.A. Baidyk T.N., et-al. Micromechanical engineering: A basis fot the low cost manufacturing of mechanical microdevices using microequipment J. Micromech. Microeng. 6 1996 410-425
23. Kussul, E., Baidyk, T., Kasatkina, L., Lukovich, V., 2001. Rosenblatt perceptrons for handwritten digit recognition. In: Proc. Internat. Joint Conf. on Neural Networks, Washington, USA, July 15-19, pp. 1516-1520
24. Kussul, E., Baidyk, T., Ruiz, L., Caballero, A., Velasco, G., 2002a. Development of low-cost microequipment. In: IEEE Internat. Symposium on Micromechatronics and Human Science, Nagoya, Japan, pp. 125-134
25. Kussul E. Baidyk T. Ruiz-Huerta L. Caballero A. Velasco G. Kasatkina L. Development of micromachine tool prototypes for microfactories J. Micromech. Microeng. 12 2002 795-813
26. Kuwano, H., 1996. MEMS for telecommunication systems. In: Proc. 7-th Internat. Symposium on Micro Machine and Human Science, pp. 21-28
27. LeCun Y. Bottou L. Bengio Y. Haffner P. Gradient-based learning applied to document recognition Proc. IEEE 86 11 1998 2278-2344
28. 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. In: IEEE Internat. Symposium on Micromechatronics and Human Science, pp. 203-210
29. Madni, A.M., Wan, L.A., 1998. Micro electro mechanical systems (MEMS): An overview of current state-of-the art. In: IEEE Aerospace Conf., vol. 1, pp. 421-427
30. Ofeifer, T., Dussler, G., 2002. Process observation for the assembly of hybrid micro systems. In: IEEE Internat. Symposium on Micromechatronics and Human Science, pp. 117-123
31. Ohlckers, P., Jakobsen, H., 1997. High volume production of silicon sensor microsystems for automotive applications. In: IEEE Colloquium on Assembly and Connection in Microsystems (Digest No. 1997/004), pp. 8/1-8/7
32. Ooyama, N., Kokaji, Sh., Tanaka M., et al., 2000. Desktop machining microfactory. In: Proc. 2-nd Internat. Workshop on Microfactories, Switzerland, October 9-10, pp. 14-17
33. Trimmer, W.S. (Ed.), 1997. Micromechanics and MEMS. Classsical and Seminal Papers to 1990. IEEE Press, New York, p. 701
34. Vapnik V. An overview of statistical learning theory IEEE Trans. Neural Networks 10 5 1999 988-1000
35. Whitney D. Quasi-static assembly of compliantly supported rigid parts ASME J. Dyn. Systems Meas. Control 104 1982 65-77
36. GYamamoto, Y., Hashimoto, T., Okubo, T., Itoh, T., 2001. Measurement of force sensory information for the automation of ultra-precision assembly tasks. In: IEEE/ASME Internat. Conf. on Advanced Intelligent Mechatronics Proceedings, Italy, pp. 395-400