ICIAR 2005: Image Analysis and Recognition pp 499-506 | Cite as
Cylinder Rotational Orientation Based on Circle Detection
Abstract
The paper addresses the computer vision aspects of aligning a hydraulic cylinder prior to being hooked on a conveyer by a robotic arm. The robotic arm is programmed to assume the cylinder’s clevis hole is perpendicular to the horizontal base of the stamping station; if the cylinder is not in this orientation, the arm will unsuccessfully attempt to hook the cylinder on the conveyor line, dropping it to the concrete floor. The approach is based on the use of the Hough transform for circle detection. A camera is mounted in a rotational orientation cradle and the different camera positions result in images in which the hole is seen as an ellipse that evolves to a circle as the correct angle is reached. The paper then discusses the effect of implementing circle detection on ellipses, and takes advantage of the count in the Hough parameter space that indicates the correct position. The approach has shown to be very efficient under the restrictions of positioning the cylinder in less than 35 seconds as well as achieving orientation errors less than +/- 5°.
Keywords
Image Frame Hydraulic Cylinder Correct Orientation Computer Vision System Concrete FloorPreview
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References
- 1.Hugerbuhler, N.: A Short Elementary Proof of the Mohr-Mascheroni Theorem. American Mathematical Monthly 101(8), 784–787 (1994)CrossRefMathSciNetGoogle Scholar
- 2.Gonzales, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice Hall, New Jersey (2002)Google Scholar
- 3.Nakanishi, M., Ogura, T.: Real-time Line Extraction Using a Highly Parallel Hough Transform Board. In: IEEE Proceedings International Conference on Image Processing, Santa Barbara CA, USA (1997)Google Scholar
- 4.Palmer, P., Kittler, J., Petrou, M.: Methods for Improving Line Parameter Accuracy in a Hough Transform Algorithm. In: IEE Colloquium on Hough Transforms, London, UK (1993)Google Scholar
- 5.Pui-Kin, S., Wan-Chi, S.: Object Recognition with a 2-D Hough Domain. In: IEEE International Symposium on Circuits and Systems, London, UK (1994)Google Scholar