Abstract
This paper describes a skeletonization approach that has desirable characteristics for the analysis of static handwritten scripts. We concentrate on the situation where one is interested in recovering the parametric curve that produces the script. Using Delaunay tessellation techniques where static images are partitioned into sub-shapes, typical skeletonization artifacts are removed, and regions with a high density of line intersections are identified. An evaluation protocol, measuring the efficacy of our approach is described. Although this approach is particularly useful as a pre-processing step for algorithms that estimate the pen trajectories of static signatures, it can also be applied to other static handwriting recognition techniques.
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