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The interpolation of contour pixels, with splines, of
an order greater than or equal to two, usually causes
oscillations that do not fit the original shape. To overcome this
we propose using a least squares filter before carrying out the
interpolation. This results in a good compromise between the
smoothness of the curve and the best fit to the original contour.
Representing the contour with a continuous model instead of a
discrete model has many advantages for carrying out
calculations, as for example the contour curvature, which
involves first and second order derivatives, as well as
operations that are not well defined in the discrete world. We
also present a new way of calculating FIR approximations to
filters based on B-splines. The great advantage of this
approximation in the case of least squares filter is that it does
not need downsampling. This property makes it invariant to
translations, and this is very important in classification tasks.
CitationFerrer-Arnau, Ll. [et al.]. Efficient representation of contours using splines implemented with FIR filters. A: International Conference on Next Generation Web Services Practices. "7th International Conference on Next Generation Web Services Practices". Salamanca: 2011, p. 125-128.
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