Handwritten Chinese character segmentation using a two-stage approach

Correct segmentation of handwritten Chinese characters is crucial to the successful recognition. However, because of the many difficulties involved, little work has been done in this area. In this paper, a two-stage approach is addressed to segment unconstrained handwritten Chinese character strings. A string is first coarsely segmented according to the background skeleton and vertical projection after a proper image preprocessing. At the fine segmentation stage that follows, the strokes that may contain segmentation points are first identified. The feature points are then extracted from candidate strokes and taken as segmentation point candidates through each of which a segmentation path may be formed. Geometric features are extracted and fuzzy decision rules learned from examples are used to evaluate the segmentation paths. By using this two-stage segmentation approach, we can achieve both good performance and efficiency in segmenting unconstrained handwritten Chinese characters.