Abstract
In this paper, we first derive a set of inequalities for the parameters of a Euclidean line from sample pixels, and an optimization criterion with respect to this set of constraints for the recognition of the Euclidean line. Second, using this optimization problem, we prove uniqueness and ambiguity theorems for the reconstruction of a Euclidean line. Finally, we develop a polygonalization algorithm for the boundary of a discrete shape.
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Linh, T.K., Imiya, A. (2003). Nonlinear Optimization for Polygonalization. In: Nyström, I., Sanniti di Baja, G., Svensson, S. (eds) Discrete Geometry for Computer Imagery. DGCI 2003. Lecture Notes in Computer Science, vol 2886. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39966-7_42
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DOI: https://doi.org/10.1007/978-3-540-39966-7_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20499-2
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