Segmentation of Connected Handwritten Chinese Characters Based on Stroke Analysis and Background Thinning

摘要

Segmentation of connected handwritten Chinese characters is a very difficult task in document image analysis. In this paper, a novel algorithm based on stroke analysis and background thinning is proposed to segment connected handwritten Chinese characters. The feature points, viz. end points, fork points and corner points are detected in the thinned image. The segments between feature points are considered as substrokes and are extracted. Lengths of substrokes and the topological relations between them are employed to locate connected point. A new method based on background thinning is developed to decide a proper segmentation path. The experimental results show that satisfactory performance is achieved by the presented method for segmentation of connected handwritten Chinese characters.