Affiliation:
1. Database and Multimedia Research Institute, College of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, P. R. China
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.
Publisher
World Scientific Pub Co Pte Lt
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Cited by
1 articles.
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