Genetic Algorithm-Based Brush Stroke Generation for Replication of Chinese Calligraphic Character

Abstract

This paper presents a novel brush stroke generation scheme based on Genetic Algorithms (GA) and pre-defined brush template models. The work is part of an endeavor to attempt imitating master works of famous past calligraphers. The concept is to parametrize, in some computational sense, the writing styles and techniques of certain calligraphers and then executes the results in a robot drawing platform developed in our laboratory. The present work describes the algorithmic development, simulation studies and experimentation of the GA-based stroke generation scheme upon given certain calligraphic characters. To further study the effectiveness of calligraphic writing with the robot platform, the Cross-Entropy method of the Traveling Salesman problem is incorporated to determine the sequence of stroke execution.