Title
Interpretation Of Ambiguous Zone To Improve Thinning Results Of Handwritten Chinese Characters
Abstract
The skeleton representation of characters is a fundamental step to handwriting recognition, but traditional skeletonization algorithms always produce unwanted artifacts or pattern distortions at regions with intersections or junctions of strokes. In this paper, we propose a novel method to eliminate these unreliable skeleton segments and improve the skeletonization of handwritten Chinese characters on the basis of ambiguous zone interpretation. This method consists of two main phases. In the first phase, the parts of characters which contain the distortions of skeleton, called ambiguous zones, are detected. Instead of exploiting any corner or dominant point detection, a set of feature points from the original skeleton and the contour information around them are manipulated in our approach. In the phase of interpretation, the continuity of skeleton segments of substrokes is estimated based on the minimum curvature variation criterion, and compensations are made to fix interstices of terminated skeleton segments. Finally, the distorted parts of characters are reconstructed by applying a cubic B-spline interpolation. Experimental results show that the proposed method can detect ambiguous zones with arbitrary shapes accurately, and produce skeletons that are close to human perceptions.
Year
DOI
Venue
2010
10.1142/S0218001410007932
INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE
Keywords
Field
DocType
Thinning algorithm, ambiguous zone, skeleton, fork point, handwriting recognition
Chinese characters,Computer vision,Morphological skeleton,Curvature,Pattern recognition,Dominant point detection,Interpolation,Handwriting recognition,Skeletonization,Artificial intelligence,Skeleton (computer programming),Mathematics
Journal
Volume
Issue
ISSN
24
2
0218-0014
Citations 
PageRank 
References 
1
0.35
18
Authors
3
Name
Order
Citations
PageRank
Zhewen Su1101.51
Zhongsheng Cao2323.64
Yuanzhen Wang38611.78