Generating new styles of Chinese strokes based on statistical model

Chinese calligraphy is one of the most important Chinese arts: a form of entertainment as well as an embodiment of figurative thinking. In this paper, a statistical model-based approach to generating new styles of Chinese character strokes is proposed. Original calligraphy samples are aligned in a common co-ordinate frame and a training set consisting of landmarks is generated semi-automatically. The most significant features of the training set are extracted and a statistical model is built in order to generate strokes in new styles. The Bezier curve is used to fit the discrete contour data.