Digitization of handwritten document is important for better processing and storage. But people wish to have their own personal handwriting as font because Personal font style gives a personal touch and make the document more eye-catching. Font generation is a process of generation of a handwritten document-based writing characteristic which is specific to user’s writing style. In this paper comparative study of font generation techniques has been presented for different languages such as English, Bangla, and Chinese. We also compare different methods like RNN, a Macro structure model, LSTM etc. which were used for font generation in different languages. Different parameters have been considered for regenerating someone’s font like character glyph, character space and connection style.
Font Generation, Glyph synthesis, RNN, LSTM
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