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Minimum description length arc spline approximation of digital curves

Maier, G. ; Janda, F. ; Schindler, A.

2012 19th IEEE International Conference on Image Processing, 2012, p.1869-1872

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Título:
Minimum description length arc spline approximation of digital curves
Autor: Maier, G. ; Janda, F. ; Schindler, A.
Assuntos: Approximation algorithms ; Approximation methods ; arc spline ; circular arc ; contour approximation ; Data models ; digital curve ; Image segmentation ; minimum description length ; Piecewise linear approximation ; Shape ; Splines (mathematics)
É parte de: 2012 19th IEEE International Conference on Image Processing, 2012, p.1869-1872
Descrição: We present a method for an unsupervised two model approximation of digital curves. For any maximum tolerance, we obtain the minimum number of smoothly joined circular arcs and line segments. The breakpoints of the resulting curve are neither restricted to be pixel discrete nor they have to be chosen from a finite set of points. Instead, they are computed automatically. This has a considerably positive effect on the number of segments. In addition, we present a very efficient way to encode the approximating curve. Thus, we achieve the minimum description length for any tolerance. The performance of the proposed method is illustrated by different examples including characteristics as the description length, the fitting error and the length-angle representation.
Editor: IEEE
Idioma: Inglês

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