Handwritten font generation is important for preserving cultural heritage and
creating personalized designs. It adds an authentic and expressive touch to
printed materials, making them visually appealing and establishing a stronger
connection with the audience. This paper aims to design a framework for
generating handwritten fonts in the Gujarati script, mimicking the variation of
human handwriting. The proposed font generation model consists of a learning
phase and a generation phase. In the learning phase, Gujarati scripts are
analyzed, and rules for designing each character are formulated. This ruleset
involves the concatenation of strokes in a stroke-based manner, ensuring visual
consistency in the resulting glyphs. The generation phase involves the user
providing a small subset of characters, and the system automatically generates
the remaining character glyphs based on extracted strokes and learned rules,
resulting in handwritten Gujarati fonts. The resulting character glyphs are
converted into an open-type font using the FontForge tool, making them
compatible with any Gujarati editor. Both subjective and objective evaluations
are conducted to assess the synthesized images and fonts. Subjective evaluation
through user studies provides feedback on quality and visual appeal, achieving
an overall accuracy of 84.84%. Notably, eleven characters demonstrated a
success ratio above 90%. Objective evaluation using an existing recognition
system achieves an overall accuracy of 84.28% in OCR evaluation. Notably,
fifteen characters had a success ratio of 80% or higher.

设计了一个用于生成手写古吉拉特字体的框架，通过学习阶段和生成阶段实现，用户提供一小部分字符，系统根据学习的规则和提取的笔画自动生成手写古吉拉特字体，评估结果显示主观评估准确率为 84.84%，客观评估准确率为 84.28%。