Handwritten Chinese Character Font Generation Based on Stroke Correspondence

In this paper, we investigate a novel method for an individual's handwritten Chinese character font generation, using stroke correspondence between the reference character database and the compressed character database, by vector quantization. Chinese characters are composed of a combination of radicals. A radical may be separated into several strokes, with each stroke corresponding to two or more common strokes. By paying attention to the characteristics of Chinese characters and the strokes that form them, we consider each stroke to be a vector and compress the stroke pattern using vector quantization. A compression rate of 1.27% is achieved by the vector quantization. We performed the evaluation experiments using both subjective and objective criteria involving 26 subjects and demonstrated that fonts generated successfully reflect the user's individual handwriting.