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Automatic Generation of Typographic Font From Small Font Subset.

Tomo Miyazaki, Tatsunori Tsuchiya, Yoshihiro Sugaya

    IEEE Computer Graphics and Applications
    |August 6, 2019
    PubMed
    Summary

    This study introduces an automated font generation method to create thousands of characters from a small sample. This innovation significantly reduces the time and cost associated with font creation, especially for complex scripts.

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    Area of Science:

    • Computer Graphics
    • Digital Typography
    • Artificial Intelligence

    Background:

    • Automated font generation is crucial for digital content, especially for languages with extensive character sets like Japanese.
    • Current font creation relies heavily on manual labor by professional typographers, incurring substantial time and financial costs.
    • Existing automated methods struggle with fonts featuring distinctive or complex stroke designs.

    Purpose of the Study:

    • To develop a novel method for automatically generating a complete typographic font from a limited subset of character images.
    • To address the limitations of existing methods in handling diverse and complex font styles.
    • To enable the creation of large character sets efficiently and cost-effectively.

    Main Methods:

    • A novel approach for generating missing characters within a target font based on a provided small subset.
    • The method is designed to be versatile, accommodating various font styles, including those with unique stroke characteristics.
    • Implementation involved generating characters beyond the initial subset to ensure a complete font.

    Main Results:

    • Successfully generated 2965 characters across 47 different fonts.
    • The generated characters were validated through both objective and subjective evaluations.
    • Evaluations confirmed a high degree of similarity between the automatically generated characters and the original font designs.

    Conclusions:

    • The proposed method offers an effective solution for automated font generation, significantly reducing manual effort.
    • The technique demonstrates robustness in handling diverse font styles, including challenging designs with distinctive strokes.
    • This advancement has the potential to streamline font production for large character sets, making font creation more accessible.