Here, we have proposed the complete font generation model that has two main phases: A learning phase and a generation phase, in the learning phase we created rules set for generating Gujarati characters that include information like size, a position of strokes, width, endpoints, junction point, etc. Our study aims to generate Gujarati handwritten font in personal handwriting style using stroke-based synthesis and style learning. Another is shape simulation, in which characters’ glyph can act as input elements and synthesized the writing based on the glyph.
It has two approaches: Movement simulation, where neuromuscular hand movement is the key feature to synthesis the writing. It can be achieved by the concept of handwriting synthesis. In this era, people want a handwriting style personal font for communication with the goal that a document or message can be displayed as they are written by their own hands.