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An Adaptive Local Smoothing for Contour Figure Approximation

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Scale-Space Theories in Computer Vision (Scale-Space 1999)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1682))

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Abstract

We propose a method for contour figure approximation which does not assume the shape of primitives for contours. By smoothing out only local details by curvature flow process, a given contour figure is ap- proximated. The amount of smoothing is determined adaptively based on the sizes of the local details. To detect local details and to determine the amount of the local smoothing, the method uses the technique of the scale space analysis. Experimental results show that this approxima- tion method has preferable properties for contour figure recognition, e.g. only finite number of approximations are obtained from a given contour figure.

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References

  1. Koichiro Deguchi and Hidekata Hontani. Multiscale Contour Approximation Based on Scale Space Analysis with A Stable Gaussian Smoothing. In 2nd International Workshop on Visual Form, Capri, Italy, pages 139–148, 1994.

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© 1999 Springer-Verlag Berlin Heidelberg

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Hontani, H., Deguchi, K. (1999). An Adaptive Local Smoothing for Contour Figure Approximation. In: Nielsen, M., Johansen, P., Olsen, O.F., Weickert, J. (eds) Scale-Space Theories in Computer Vision. Scale-Space 1999. Lecture Notes in Computer Science, vol 1682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48236-9_47

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  • DOI: https://doi.org/10.1007/3-540-48236-9_47

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66498-7

  • Online ISBN: 978-3-540-48236-9

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