Font generation based on style and character structure analysis using diffusion models

   The article discusses the role of generative neural networks in the development and optimization of fonts which play a key role in creating aesthetically attractive and functional designs. The main attention is paid to licensing restrictions and insufficient availability of fonts for various world languages, which creates difficulties for designers and typographers in the process of creating text materials. The novelty of the approach lies in the use of the diffusion model as a generative neural network for automatic font creation, including missing glyphs for languages not supported by standard fonts. To solve the tasks set, a diffusion model has been developed which is an algorithm for generating fonts based on the analysis of patterns in the structure of symbols and the logic of their construction. The model is integrated into an application that automates the process of creating font layouts, allowing users to generate new glyphs and fonts tailored to specific language needs. This technique includes preliminary data preparation, network training, and subsequent character generation that mimic the style and composition of the original fonts. During the experiments, the diffusion model demonstrated a high ability to generate high-quality font characters visually similar to the original samples. Font sets with a limited set of characters were used as source data, which allowed us to evaluate the capabilities of the model to create missing glyphs for various languages. The results showed that the developed model successfully reproduces the stylistic features of the original font, which confirms its potential for application in the development of font solutions for global use. The proposed method of font generation is of interest to specialists working in the field of design, typography, and the creation of text materials for various language audiences. The results obtained can be useful when creating fonts intended for use in multilingual projects that require the presence of missing characters.

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