Abstract
This paper focuses on an ill-posed problem of recovering a human-like drawing order from static handwritten images with double-traced lines. The problem is analyzed and solved by employing a method based on the graph theoretic approach. Then, a main issue is to obtain the smoothest path of stroke from a graph model corresponding to input image. First, we develop an index on double-traced lines “D-line index” by employing the spline curves. Then, it is shown that the graph is transformed to a semi-Eulerian graph. The restoration problem reduces to maximum weight matching problem and is solved by a probabilistic tabu search. We examine the effectiveness and usefulness by some experimental studies.
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Nagoya, T., Fujioka, H. (2013). Recovering Human-Like Drawing Order from Static Handwritten Images with Double-Traced Lines. In: Park, J.J., Barolli, L., Xhafa, F., Jeong, H.Y. (eds) Information Technology Convergence. Lecture Notes in Electrical Engineering, vol 253. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-6996-0_99
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DOI: https://doi.org/10.1007/978-94-007-6996-0_99
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-6995-3
Online ISBN: 978-94-007-6996-0
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