Abstract
This paper describes investigation results on the design of a real time, computer vision based system for automatic inspection of filter components in a manufacturing line. The problem involves reasoning about an object’s 3D structure from 2D images. In computer vision, this is normally referred to as a 3D-2D problem. In this paper, we first present a geometrical analysis of image correspondence vectors synthesised into a single coordinate frame. The analysis is based on geometrical considerations that are fundamentally different from analytical, perspective, or epipolar geometries. The camera setup stems from the geometrical implications of such analysis and from the given background knowledge of the task within the context of the production line. We then describe a novel geometrical algorithm to estimate parameters of interest that include depth estimation and the position and orientation of the camera in world coordinate frame. The algorithm provides the closed form solution to all estimated parameters making full use of distance between feature vectors and angle information. For a comparative study of algorithm performance, we also developed an algorithm based on epipolar geometry. Experimental results show that the geometrical algorithm performs significantly better than the algorithm based on epipolar geometry.
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References
Mitiche, A., Aggarwal, J.K.: A computational analysis of time-varying images. In: Yuong, T.Y., Fu, K.S. (eds.) Handbook of Pattern Recognition and Image Processing. Academic Press, London (1986)
Weng, J., Huang, T.S., Ahuja, N.: Motion and structure from two projective views: algorithms, error analysis and error estimation. IEEE Trans. on Pattern Analysis and Mach. Intell. 11(5), 451–476 (1989)
Tsai, R.Y., Huang, T.S.: Uniqueness and estimation of three-dimensional motion parameters of rigid objects with curved surfaces. IEEE Trans. on Pattern Analysis and Mach. Intell. 6(1), 13–27 (1984)
Huang, T.S., Faugeras, O.D.: Some properties of the E matrix in two-view motion estimation. IEEE Trans. on Pattern Analysis and Mach. Intell. 11(12), 1310–1312 (1990)
Haralick, R.M., Chung-Nan Lee, H.J., Zhuang, X., Vaidya, V.G., Kim, M.A.: Pose estimation from corresponding point data. IEEE Trans. on Pattern Analysis and Mach. Intell. 19(6), 1426–14461 (1989)
Linnainmaa, S., Harwood, D., Davis, L.S.: Pose determination of a three-dimensional object using triangular pairs. IEEE Trans. on Pattern Analysis and Mach. Intell. 10(5), 634–647 (1987)
Wolf, P.R.: Elements of photogrammetry. McGraw-Hill, New York (1974)
Ganapathy, S.: Decomposition of transformation matrices for robot vision. Pattern Recognition Letters 2, 401–412 (1989)
Fischler, M., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Communications of ACM 24(6), 381–395 (1981)
Joseph, S.H.: Optimal pose estimation in two and three dimensions. Comp. Vision and Image Understanding 73(2), 215–231 (1999)
Oberkampf, D., DeMenthon, D.F., Davis, L.S.: Iterative pose estimation using coplanar feature points. Comp. Vision and Image Understanding 63(3), 495–511 (1996)
Araujo, H., Carceroni, R.L., Brown, C.M.: A fully projective formulation to improve the accuracy of Lowe’s pose estimation algorithm. Comp. Vision and Image Understanding 71(2), 227–238 (1998)
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© 1999 Springer-Verlag Berlin Heidelberg
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Rodrigues, M.A., Liu, Y. (1999). A Novel 3D-2D Computer Vision Algorithm for Automatic Inspection of Filter Components. In: Imam, I., Kodratoff, Y., El-Dessouki, A., Ali, M. (eds) Multiple Approaches to Intelligent Systems. IEA/AIE 1999. Lecture Notes in Computer Science(), vol 1611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-48765-4_60
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DOI: https://doi.org/10.1007/978-3-540-48765-4_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66076-7
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