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• W2096252661 endingPage "1737" @default.
• W2096252661 startingPage "1724" @default.
• W2096252661 abstract "Restoration of writing order from a single-stroked handwriting image can be seen as the problem of finding the smoothest path in its graph representation. In this paper, a 3-phase approach to restore a writing order is proposed within the framework of the edge continuity relation (ECR). In the initial, local phase, in order to obtain possible ECRs at an even-degree node, a neural network is used for the node of degree 4 and a theoretical approach is presented for the node of degree higher than 4 by introducing certain reasonable assumptions. In the second phase, we identify double-traced lines by employing maximum weighted matching. This makes it possible to transform the problem of obtaining possible ECRs at odd-degree node to that at even-degree node. In the final, global phase, we find all the candidates of single-stroked paths by depth first search and select the best one by evaluating SLALOM smoothness. Experiments on static images converted from online data in the Unipen database show that our method achieves a restoration rate of 96.0 percent" @default.
• W2096252661 created "2016-06-24" @default.
• W2096252661 creator A5054690646 @default.
• W2096252661 creator A5065222593 @default.
• W2096252661 creator A5072861783 @default.
• W2096252661 date "2006-11-01" @default.
• W2096252661 modified "2023-10-16" @default.
• W2096252661 title "A Framework Toward Restoration of Writing Order from Single-Stroked Handwriting Image" @default.
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• W2096252661 doi "https://doi.org/10.1109/tpami.2006.216" @default.
• W2096252661 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/17063679" @default.
• W2096252661 hasPublicationYear "2006" @default.
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