Abstract
In this paper, we present a method for correcting a skeleton-based vectorization. The method robustly segments the skeleton of an image into basic features, and uses these features to reconstruct analytically all the junctions. It corrects some of the topological errors usually brought by polygonal approximation methods, and improves the precision of the junction points detection.
We first give some reminders on vectorization and explain what a good vectorization is supposed to be. We also explain the advantages and drawbacks of using skeletons. We then explain in detail our correction method, and show results on cases known to be problematic.
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Hilaire, X., Tombre, K. (2002). Improving the Accuracy of Skeleton-Based Vectorization. In: Blostein, D., Kwon, YB. (eds) Graphics Recognition Algorithms and Applications. GREC 2001. Lecture Notes in Computer Science, vol 2390. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45868-9_24
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DOI: https://doi.org/10.1007/3-540-45868-9_24
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