In the production line of printed circuit boards (PCB), quality control requires constant counting and recording of the number of boards which, in some special cases, is done by workers in the factory. This form of counting consumes labor and time, not to mention the high error rate. In this paper, an automatic method to count PCBs is proposed. With the use of image processing techniques, the number of PCBs can be non-destructively calculated as they pass through the production line, which will effectively improve the production efficiency. The first step of the proposed system is to take a picture of a stack of PCBs using a digital camera. The captured image is transformed to a gray level picture and processed by a noise removal algorithm to improve the proposed mechanism’s precision. The output of the counting algorithm includes PCB count and confidence level. In practical applications, the confidence level can help people to on-line diagnose erroneous counting and correct it when the visualization counting system fails to accurately differentiate the boards.
[3] Chang, C. Y., Xu, J. Y. and Cai, F. R., “The Applications of Position Monitoring with Enhanced Image Processing,” Journal of Cheng Shiu University, Vol. 18, pp. 147160 (2005).
[4] Windyga, P. S., “Fast Impulsive Noise Removal,” IEEE Transactions on Image Processing, Vol. 10, pp. 173179 (2001).
[5] Damil, N., Bakar, Z. A. and Sembok, T. M. T., “A Comparison of Noise Removal Techniques in Songket Motif Images,” Proc. of the International Conference on Computer Graphics, Imaging and Visualization, pp. 139143 (2004).
[6] Gonzalez, R. C. and Woods, R. E., Digital Image Processing, Prentice Hall, London (2002).
[7] Kuo, C. H., Wu, P. H. and Wang, T. S., “On the Construction of a Color Model for Real-time Visual Moving Objects Segmentation,” The Tamkang Journal of Science and Engineering, Vol. 8, pp. 8798 (2005).
[8] Terada, K., Yoshida, D., Oe, S. and Yamaguchi, J., “A Method of Counting the Passing People by Using the Stereo Images,” International Conference on Image Processing, Vol. 2, pp. 338342 (1999).
[9] Tsuchikawa, M., Sato, A., Koike, H. and Tomono, A., “A Moving-Object Extraction Method Robust Against Illumination Level Changes for a Pedestrian Counting System,” International Symposium on Computer Vision, pp. 563568 (1995).
[10] Chen, T. H., “An Automatic Bi-Directional PassingPeople Counting Method Based on Color Image Processing,” International Carnahan Conference on Security Technology, pp. 200207 (2003).
[11] Tremsin, A. S., Siegmund, O. H. W., Vallerga, J. V., Hull, J. S. and Abiad, R., “Cross Strip Readouts for Photon Counting Detectors with High Spatial and Temporal Resolution,” IEEE Transactions on nuclear science, Vol. 51, pp. 17071711 (2004).
We use cookies on this website to personalize content to improve your user experience and analyze our traffic. By using this site you agree to its use of cookies.
