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

We describe a new method for representation of an image pattern, which we call the reduced special interval graph (RSIG). Any binary image pattern can be easily converted into a RSIG. Based on the RSIG, we can enlarge the scope of vision and process a much greater zone of the image. This helps us properly extract the feature of the image and identify the image pattern. We apply the RSIG to help us extract the strokes of Chinese characters by incorporating some knowledge about the structure of Chinese characters. We found this method can not only heuristically extract strokes but also heuristically eliminate noises including those added to strokes for the artistic sake. Experimental results reveal that the method based on the RSIG can extract the strokes of Chinese characters effectively and efficiently. Moreover, the RSIG can be applied to many other application areas, and it is an effective representation method in pattern recognition and image processing. >

[1]  Fang-Hsuan Cheng,et al.  Recognition of Handwritten Chinese Characters by Modified Hough Transform Techniques , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Fang-Hsuan Cheng,et al.  Research on Chinese OCR in Taiwan , 1991, Int. J. Pattern Recognit. Artif. Intell..

[3]  Wen-Hsing Hsu,et al.  Classifying Method Using Structural Analysis and Total Length for Handwritten Chinese Characters , 1985 .

[4]  Fang-Hsuan Cheng,et al.  Three Stroke Extraction Methods for Recognition of Handwritten Chinese Characters , 1986 .

[5]  Kazuhiko Yamamoto,et al.  Research on Machine Recognition of Handprinted Characters , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Jun S. Huang,et al.  Stroke segmentation by bernstein-bezier curve fitting , 1990, Pattern Recognit..

[7]  Minsoo Suk,et al.  On machine recognition of hand-printed Chinese characters by feature relaxation , 1988, Pattern Recognit..

[8]  V. K. Govindan,et al.  Character recognition - A review , 1990, Pattern Recognit..

[9]  Chengjian Sun,et al.  Recognizing restricted handwritten Chinese characters by structure similarity method , 1990, Pattern Recognit. Lett..

[10]  Hiroshi Nagahashi,et al.  A Description Method of Handprinted Chinese Characters , 1979, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Wen-Hsing Hsu,et al.  Stroke Extraction and Matching Methods for Handwritten Chinese Characters Recognition , 1984 .

[12]  Yung-Sheng Chen,et al.  Stroke Relation Coding - a New Approach to the Recognition of Multi-Font Printed Chinese Characters , 1988, Int. J. Pattern Recognit. Artif. Intell..

[13]  Zhengwen Zhang,et al.  A research on printed Chinese character recognition based on stroke features with optical/digital hybrid realization , 1988, ICPR.

[14]  Kim-Teng Lua,et al.  A new approach to stroke and feature point extraction in Chinese character recognition , 1991, Pattern Recognit. Lett..

[15]  Hiromitsu Yamada,et al.  Recognition of Hand-Printed Chinese Characters and the Japanese Cursive Syllabary , 1992 .

[16]  Zhang Zhengwen,et al.  A research on printed Chinese character recognition based on stroke features with optical/digital hybrid realization , 1988, [1988 Proceedings] 9th International Conference on Pattern Recognition.

[17]  Y. S. Cheung,et al.  A knowledge-based stroke-matching method for Chinese character recognition , 1987, IEEE Transactions on Systems, Man, and Cybernetics.

[18]  Fang-Hsuan Cheng,et al.  Recognition of Handwritten Chinese Characters by Structure Analysis of Strokes , 1985 .

[19]  Lin-Yu Tseng,et al.  An efficient knowledge-based stroke extraction method for multi-font chinese characters , 1992, Pattern Recognit..

[20]  M. Golummc Algorithmic graph theory and perfect graphs , 1980 .