Consistently and correctly writing out such huge amounts of characters is usually an impossible mission for ordinary people. For example, the official standard GB18030-2000 for commercial font products consists of 27,533 Chinese characters.
A Java Implementation is developed to read a document image of user handwritten Chinese characters, and make a vector font of these handwritten Chinese characters. Generating personal handwriting fonts with large amounts of characters is a boring and time-consuming task. Rather than to create glyphs of characters one by one according to their codepoints, people create glyphs incrementally in an on-demand manner. We present a new method to create font in a batch mode. In this study, we performed a process reengineering in font generation. However, it is not easy for ordinary users to customize a font of their personal handwritings. An improved network architecture is proposed for learning and generation of personal hand-writing style fonts based on small character set, and the effectiveness of the model for generating personalHandwriting style font with relatively small data size is revealed. This is especially true in Chinese calligraphy. It is commonly believed that handwritings can reflect one's personality, emotion, feeling, education level, and so on. Many fonts have been developed so that product designers can choose unique fonts to demonstrate their idea gracefully. Nevertheless, text is still the most popular media for people to communicate with others. Today, digital multimedia messages have drawn more and more attention due to the great achievement of computer and network techniques.