Title
Interpretation of Ambiguous Zone in Handwritten Chinese Character Images Using Bayesian Network
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.
Year
DOI
Venue
2009
10.1007/978-3-642-01513-7_41
ISNN (3)
Keywords
Field
DocType
continuous pair,bayesian belief network,handwritten image,standard handwritten chinese text,dynamic information,novel method,bayesian network,ambiguous zone,handwritten chinese character,essential step,initial phase
Graph,Curvature,Pattern recognition,Computer science,Handwriting recognition,Bayesian network,Artificial intelligence,Stroke extraction,Machine learning
Conference
Volume
ISSN
Citations 
5553
0302-9743
0
PageRank 
References 
Authors
0.34
11
3
Name
Order
Citations
PageRank
Zhongsheng Cao1323.64
Zhewen Su2101.51
Yuanzhen Wang38611.78