Abstract
Stereo vision technology has the poetential for measuring the dimensions of hot large forging. However, under the high temperature operation circumstance in forging workshop, it is difficult to calibrate the stereo vision sensor by the traditional calibration method, such as planar patterns method and self-calibration method. In this paper, a field calibration method of binocular stereo vision sensor is presented by virtue of projected patterns from a projector, for improving the dimensional measurement precision of large forging. The intrinsic parameters of CCD camera can be obtained by capturing the projected patterns during orthogonal movements of camera, and recognizing the feature points of patterns, while the extrinsic parameters of CCD camera is measured by detecting the distance between the feature points of patterns with the electronic theodolite. Experiments on the field calibration of camera at forging workshop are conducted. And the experimental results show that the relative error of dimensional measurement reaches 0.363%, which indicates that the proposed calibration method is effective for calibrating the dimensional measurement system of large forging.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Jia, Z.Y., Wang, B.G., Liu, W., Sun, Y.W.: An Improved Image Acquiring Method for Machine Vision Measurement of Hot Formed Parts. Journal of Materials Processing Technology 210(2), 267–271 (2010)
Tsai, R.Y.: An Efficient and Accurate Camera Calibration Technique for 3D Machine Vision. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 364–374. IEEE Press, New York (1986)
Zhang, Z.Y.: A Flexible New Technique for Camera Calibration. IEEE Trans. Pattern Analysis and Machine Intelligence. 22(11), 1330–1334 (2000)
Sun, J.H., Wu, Z.Y., Liu, Q.Z., Zhang, G.J.: Field calibration of stereo vision sensor with large FOV. Optics and Precision Engineering 17(3), 633–640 (2009) (in Chinese)
Maybank, S.J., Faugeras, O.A.: A Theory of Self-Calibration of a Moving Camera. International Journal of Computer Vision 8(2), 123–151 (1992)
Li, Y., Hung, Y.S., Lee, S.: A Stratified Self-Calibration Method for Circular Motion in Spite. Image and Vision Computing 26, 731–739 (2008)
Qian, G., Chellappa, R.: Bayesian Self-Calibration of a Moving Camera. Computer Vision and Image Understanding 95(3), 287–316 (2004)
Zhang, J.X., Duan, F.J., Ye, S.H.: Two step Method for Binocular Sensor Self-Calibration. Opto-Eletronic Engineering 25(5), 37–41 (1998)
Zhang, G.J.: Machine Vision. Science Press, Beijing (2005) (in Chinese)
Ma, S.D.: A Self-Calibration Technique for Active Vision System. IEEE Transactions on Robotics and Automation 12(1), 114–120 (1996)
Yang, C.J., Wang, W., Hu, Z.Y.: An Active Vision Based Camera Intrinsic Parameters Self-Calibration Technique. Chinese Journal of Computers 21(5), 428–435 (1998) (in Chinese)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, London (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liu, W., Du, J., Wang, B., Jia, X., Liu, S., Jia, Z. (2010). Field Calibration Method of Camera for Measuring the Dimensions of Large Forging. In: Liu, H., Ding, H., Xiong, Z., Zhu, X. (eds) Intelligent Robotics and Applications. ICIRA 2010. Lecture Notes in Computer Science(), vol 6425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16587-0_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-16587-0_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16586-3
Online ISBN: 978-3-642-16587-0
eBook Packages: Computer ScienceComputer Science (R0)