Title :
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
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;
Conference_Titel :
Document Analysis and Recognition, 1997., Proceedings of the Fourth International Conference on
Conference_Location :
Ulm
Print_ISBN :
0-8186-7898-4
DOI :
10.1109/ICDAR.1997.619843
