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A Framework Toward Restoration of Writing Order from Single-Stroked Handwriting Image
November 2006 (vol. 28 no. 11)
pp. 1724-1737
ASCII Text
x 
 
Yu Qiao, Mikihiko Nishiara, Makoto Yasuhara, "A Framework Toward Restoration of Writing Order from Single-Stroked Handwriting Image," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 11, pp. 1724-1737, November, 2006.
 
 
BibTex
x
 
@article{ 10.1109/TPAMI.2006.216,
author = {Yu Qiao and Mikihiko Nishiara and Makoto Yasuhara},
title = {A Framework Toward Restoration of Writing Order from Single-Stroked Handwriting Image},
journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence},
volume = {28},
number = {11},
issn = {0162-8828},
year = {2006},
pages = {1724-1737},
doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2006.216},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Pattern Analysis and Machine Intelligence
TI - A Framework Toward Restoration of Writing Order from Single-Stroked Handwriting Image
IS - 11
SN - 0162-8828
SP1724
EP1737
EPD - 1724-1737
A1 - Yu Qiao,
A1 - Mikihiko Nishiara,
A1 - Makoto Yasuhara,
PY - 2006
KW - Handwriting recognition
KW - writing order restoration
KW - edge continuity relation
KW - temporal information
KW - graph matching
KW - Euler path.
VL - 28
JA - IEEE Transactions on Pattern Analysis and Machine Intelligence
ER -
 
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.

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Index Terms:
Handwriting recognition, writing order restoration, edge continuity relation, temporal information, graph matching, Euler path.
Citation:
Yu Qiao, Mikihiko Nishiara, Makoto Yasuhara, "A Framework Toward Restoration of Writing Order from Single-Stroked Handwriting Image," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 11, pp. 1724-1737, Nov. 2006, doi:10.1109/TPAMI.2006.216
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