Abstract
The maxima of Curvature Scale Space (CSS) image have already been used to represent 2-D shapes under affine transforms. Since the CSS image employs the arc length parametrisation which is not affine invariant, we expect some deviation in the maxima of the CSS image under general affine transforms.
In this paper we examine the advantage of using affine length rather than arc length to parametrise the curve prior to computing its CSS image. The parametrisation has been proven to be invariant under affine trans- formation and has been used in many affine invariant shape recognition methods.
The CSS representation with affine length parametrisation has been used to find similar shapes from a large prototype database.
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© 1999 Springer-Verlag Berlin Heidelberg
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Abbasi, S., Mokhtarian, F. (1999). Curvature Scale Space with Affine Length Parametrisation. 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_39
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DOI: https://doi.org/10.1007/3-540-48236-9_39
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