Analysis of stroke structures of handwritten Chinese characters

Most handwritten Chinese character recognition systems suffer from the vari ations in geometrical features for different writing styles. The stroke str uctures of different styles have proved to be more consistent than geometri cal features. In an on-line recognition system, the stroke structure can be obtained according to the sequences of writing via a pen-based input devic e such as a tablet. But in an off-line recognition system, the input charac ters are scanned optically and saved as raster images, so the stroke struct ure information is not available. In this paper, we propose a method to ext ract strokes from an off-line handwritten Chinese character. We have develo ped four new techniques: 1) a new thinning algorithm based on Euclidean dis tance transformation and gradient oriented tracing, 2) a new line approxima tion method based on curvature segmentation, 3) artifact removal strategies based on geometrical analysis, and 4) stroke segmentation rules based on s plitting, merging and directional analysis. Using these techniques, we can extract and trace the strokes in an off-line handwritten Chinese character accurately and efficiently.