DocumentCode :
2462160
Title :
Genetic Algorithm-Based Brush Stroke Generation for Replication of Chinese Calligraphic Character
Author :
Kwok, Ka Wai ; Wong, Sheung Man ; Lo, Ka Wah ; Yam, Yeung
Author_Institution :
Chinese Univ. of Hong Kong, Shatin
fYear :
0
fDate :
0-0 0
Firstpage :
1057
Lastpage :
1064
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.
Keywords :
art; entropy; genetic algorithms; robots; travelling salesman problems; Chinese calligraphic character; brush stroke generation; calligraphic writing; character replication; cross-entropy method; genetic algorithm; pre-defined brush template models; robot drawing platform; stroke execution; traveling salesman problem; writing styles; Art; Character generation; Computational modeling; Genetic algorithms; Ink; Laboratories; Painting; Robot kinematics; Traveling salesman problems; Writing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
Type :
conf
DOI :
10.1109/CEC.2006.1688426
Filename :
1688426
Link To Document :
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