Robust stroke segmentation method for handwritten Chinese character recognition

Author

Liu, Ke ; Huang, Yea S. ; Suen, Ching Y.

Author_Institution

Centre for Pattern Recognition & Machine Intelligence, Concordia Univ., Montreal, Que., Canada

Volume

1

fYear

1997

fDate

18-20 Aug 1997

Firstpage

211

Abstract

Presents a robust thinning-based method for the segmentation of strokes from handwritten Chinese characters. A new set of feature points is proposed for the analysis of skeleton images. A geometrical graph-based approach is developed for the analysis of strokes. A novel criterion is proposed for the identification of the fork points in a skeleton image which correspond to the same joint points in the original character image. Experimental results show that the proposed method is effective

Keywords

computational geometry; edge detection; feature extraction; handwriting recognition; image segmentation; optical character recognition; feature points; fork point identification; geometrical graph based approach; handwritten Chinese character recognition; joint points; robust stroke segmentation method; skeleton image analysis; stroke analysis; thinning method; Character recognition; Image analysis; Image segmentation; Joints; Optical character recognition software; Optical distortion; Robustness; Shape; Skeleton; Smoothing methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on

Conference_Location

Ulm

Print_ISBN

0-8186-7898-4

Type

conf

DOI

10.1109/ICDAR.1997.619843

Filename

619843