Abstract
In this paper, we propose a cylinder detection approach based on curvature filtering and normal clustering. We first estimate the curvature of the vertexes on each triangle, reserve these triangles which have the characteristics of a cylinder, then the triangles are clustered by the normal. Then all the triangles are transformed onto a new coordinate system, which the Z axis is parallel to the normal. Finally, the cylinders are detected by the Hough transformation in the 2D plane. The experimental results show that our proposed algorithm has good performance.
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© 2014 Springer International Publishing Switzerland
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Gao, Y., Wu, L., Mao, Y., Wang, J. (2014). A Curvature Filter and Normal Clustering Based Approach to Detecting Cylinder on 3D Medical Model. In: Ooi, W.T., Snoek, C.G.M., Tan, H.K., Ho, CK., Huet, B., Ngo, CW. (eds) Advances in Multimedia Information Processing – PCM 2014. PCM 2014. Lecture Notes in Computer Science, vol 8879. Springer, Cham. https://doi.org/10.1007/978-3-319-13168-9_23
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DOI: https://doi.org/10.1007/978-3-319-13168-9_23
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-13167-2
Online ISBN: 978-3-319-13168-9
eBook Packages: Computer ScienceComputer Science (R0)