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We propose a geometric approach to extract local properties of digital curves. This approach uses the notion of blurred segment 1. It is an extension of Reveillès' arithmetical approach 2 on discrete lines, more flexible, to take into account noise in digital images. This notion is also extended to the 3D space. Algorithms are presented to decompose a curve into a sequence of maximal blurred segments. A curvature estimator for 2D and 3D curves is proposed relying on this decomposition as well as a torsion estimator for 3D curves. All these estimators can naturally work with disconnected curves. They prove their efficiency in experiments and in comparisons with some well-known methods of the literature. [ABSTRACT FROM AUTHOR]

A new very efficient linear algorithm for the segmentation of 8-connected digital curves is given. The simplicity comes from a definition of digital lines using a linear double diophantine inequality. A complete Pascal source code is given. [ABSTRACT FROM AUTHOR]