Stroke extraction of handwritten Chinese character based on modified polygonal approximation

1994 ◽  
Author(s):  
Hon-Fai Yau ◽  
Bor-Shenn Jeng ◽  
Ming-Wen Chang ◽  
Chi-Jain Wen ◽  
Char-Shin Miou ◽  
...  
Keyword(s):  
Chinese Character ◽  
Polygonal Approximation ◽  
Stroke Extraction

A NEW STROKE EXTRACTION METHOD OF CHINESE CHARACTERS

2001 ◽  
Vol 15 (04) ◽  
pp. 707-721 ◽  
Author(s):  
XINGMING SUN ◽  
LIHUA YANG ◽  
Y. Y. TANG ◽  
YUNFA HU
Keyword(s):  
Information Processing ◽  
Character Recognition ◽  
Extraction Method ◽  
Chinese Character ◽  
Document Analysis ◽  
Chinese Characters ◽  
Stroke Extraction ◽  
Novel Method ◽  
And Storage ◽  
Document Compression

Stroke extraction of Chinese characters plays an important role in Chinese character information processing such as character recognition, document analysis, document compression and storage, font automation and so on. By analyzing the structure of Chinese characters deeply, this paper developed a novel method to extract strokes of Chinese characters directly from the original character pattern image. Two theorems, eight rules and an algorithm for stroke extraction of Chinese characters are presented. This method can overcome the difficulties encountered in disposing the intersection or connection of different strokes, and can eliminate noises successfully. Our experiments have shown that this method can extract strokes both accurately and efficiently.

A ROBUST STROKE EXTRACTION METHOD FOR HANDWRITTEN CHINESE CHARACTERS

1994 ◽  
Vol 08 (05) ◽  
pp. 1223-1239 ◽  
Author(s):  
HONG-DE CHANG ◽  
JHING-FA WANG
Keyword(s):  
Character Recognition ◽  
Extraction Method ◽  
Chinese Character ◽  
Extraction Procedure ◽  
Analysis Method ◽  
Crossing Numbers ◽  
Knowledge Based ◽  
Stroke Extraction ◽  
Attributed Graph ◽  
Connection Relation

The stroke analysis method is an effective approach for handwritten Chinese character recognition. But as we know, it is very difficult to accurately extract the strokes. In this paper, a robust stroke extraction method is proposed. First, smoothing and thinning processes are applied to smooth the shape and to obtain the skeleton of the observed character. Then the end point, internal point and fork point are detected by calculating their own crossing numbers while the corner points are determined by a knowledge-based iterative method. Virtual-end-points are introduced for separating a stroke into a certain number of line segments without losing the connection relations among them. By representing each line segment as a vertex and the connection relation of two segments as an edge, the observed character can be represented by an attributed graph. Finally, a stroke extraction procedure is proposed to extract the strokes from the global structures of the character. After each stroke of a character is extracted, the cross points can also be determined. Experimental results have shown that the proposed method is more effective than the other methods.3,5−6

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