Given the large number and complexity of Chinese characters, pattern matching based on structural decomposition and analysis is believed to be necessary and essential to off-line character recognition. This paper proposes a new model of stroke extraction for Chinese characters. One problem for stroke extraction is how to extract primary strokes. Another major problem is to solve the segmentation ambiguities at intersection points. We use the degree information and the stroke continuation property to tackle these two problems. The proposed model can be used to extract strokes from both printed and handwritten character images.