Abstract
Interpretation of ambiguous zone is an essential step to recovering dynamic information from handwritten images, which can be seen as to deduce the original motion intention of the writer at the intersection areas. This study presents a novel method to interpret ambiguous zones by constructing a Bayesian belief network. In the initial phase, a graph is built to model the character and several sample points are extracted from each sub-stroke. In the interpreting phase, each pair of sub-strokes is characterized in terms of the comparison of orientation, width, and curvature. Finally, a Bayesian belief network is established to determine the continuous pairs. A series of experiments are conducted on test samples collected from a standard handwritten Chinese text database, and the results show that the proposed method can interpret ambiguous zones effectively.
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References
Plamondon, R., Privitera, C.M.: The Segmentation of Cursive Handwriting: An Approach Based on Off-Line Recovery of the Motor-Temporal Information. IEEE Trans. Image Processing 8, 80–91 (1999)
Zou, J.J., Yan, H.: Skeletonization of Ribbon-Like Shapes Based on Regularity and Singularity Analyses. IEEE Trans. syst. Man Cybern. 31, 401–407 (2001)
Lee, C., Wu, B.: A Chinese-Character-Stroke-Extration Algorithm Based on Contour Information. Pattern Recognition 31, 651–663 (1998)
Qiao, Y., Yasuhara, M.: Recovering Dynamic Information from Static Handwritten Images. In: 9th International Workshop on Frontiers in Handwriting Recognition, pp. 118–123. IEEE Comput. Soc. Press, Los Alamitos (2004)
Qiao, Y., Nishiara, M., Yasuhara, M.: A Framework Toward Restoration of Writing Order from Single-Stroked Handwriting Image. IEEE Trans. Pattern Anal. Mach. Intell. 28, 1724–1737 (2006)
Cao, Z.S., Su, Z.W., Wang, Y.Z., Xiong, P.: A Method for Handwritten Chinese Stroke Extraction Based on Ambiguous-Zone Detection. Journal of Image and Graphics (accepted) (in Chinese)
Jäger, S.: Recovering Writing Traces in Off-Line Handwriting Recognition: Using a Global Optimization Technique. In: 13th International Conference on Pattern Recognition, pp. 150–154. IEEE Comput. Soc. Press, Los Alamitos (1996)
Nel, E.M., du Preez, J.A., Herbst, B.M.: Estimating the Pen Trajectories of Static Signatures Using Hidden Markov Models. IEEE Trans. Pattern Anal. Mach. Intell. 27, 1733–1746 (2005)
Cooper, G.F., Herskovits, E.: A Bayesian Method for the Induction of Probabilistic Networks from Data. Machine Learning 9, 309–347 (1992)
Neapolitan, R.E.: Learning Bayesian Networks. Prentice Hall, Upper Saddle River (2004)
Su, T., Zhang, T., Guan, D.: Corpus-based HIT-MW Database for Offline Recognition of General-Purpose Chinese Handwritten Text. Int. J. Doc. Anal. Recognit. 10, 27–38 (2007)
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© 2009 Springer-Verlag Berlin Heidelberg
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Cao, Z., Su, Z., Wang, Y. (2009). Interpretation of Ambiguous Zone in Handwritten Chinese Character Images Using Bayesian Network. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01513-7_41
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DOI: https://doi.org/10.1007/978-3-642-01513-7_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-01512-0
Online ISBN: 978-3-642-01513-7
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