A stroke extraction method for multifont Chinese characters based on the reduced special interval graph

1995 ◽  
Vol 25 (7) ◽  
pp. 1171-1178 ◽  
Author(s):  
Chen-Tsun Chuang ◽  
Lin Yu Tseng
Keyword(s):  
Extraction Method ◽  
Interval Graph ◽  
Chinese Characters ◽  
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.

AN APPROACH TO NATURAL STROKE EXTRACTION FOR OFF-LINE LOOSELY-CONSTRAINED HANDWRITTEN CHINESE CHARACTERS

2003 ◽  
Vol 17 (08) ◽  
pp. 1483-1513
Author(s):  
DANIEL S. YEUNG ◽  
H. S. FONG ◽  
ERIC C. C. TSANG ◽  
WENHAO SHU ◽  
XIAOLONG WANG
Keyword(s):  
Performance Tuning ◽  
Model Parameters ◽  
Chinese Characters ◽  
Personal Writing ◽  
New Approach ◽  
Stroke Extraction ◽  
Fuzzy Partitioning ◽  
Stroke Models ◽  
Matching Strategy ◽  
Ranked List

This paper proposes a new approach to extracting natural strokes from the skeletons of loosely-constrained, off-line handwritten Chinese characters. It admits the output substrokes from a previously proposed fuzzy substroke extractor as its inputs. By identifying a number of expected ambiguities which include mutual similarities, unstable touches and joint/cross distortions, fuzzy stroke models are constructed and a "hit-all" fuzzy stroke matching strategy is pursued. Fuzzy partitioning technique is used to generate a ranked list of consistent stroke sets from the set of fuzzy strokes being identified. With this approach, a maximum of 20 distinct natural stroke classes can be extracted from each input character, together with an estimate on the actual count of strokes which compose the character. Our system offers a number of performance tuning capabilities such as the computation of the fuzzy scores of each extracted stroke, the adjustment on the fuzzy stroke model parameters, and the potential of incorporating one's personal writing styles into our methodology.

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