AN IMPROVED GENERATIVE DESIGN APPROACH BASED ON GRAPH GRAMMAR FOR PATTERN DRAWING

被引：0

作者：

Liu, Yufeng ^{[1
]}

Zhou, Yangchen ^{[1
]}

Yang, Fan ^{[1
]}

Li, Song ^{[1
]}

Wu, Jun ^{[1
]}

机构：

[1] College of Information Engineering, Nanjing University of Finance and Economics, Nanjing, China

来源：

Machine Graphics and Vision | 2024年 / 33卷 / 01期

关键词：

Generative design is used to efficiently generate design solutions with powerful computational methods. Generative design based on shape grammar is currently the most commonly used approach; but it is difficult for shape grammar to formally analyze the generated pattern. Graph grammar derived from one-dimensional character grammar is mainly used for generating and analyzing abstract models of visual languages. However; there is a significant gap between the generated node-edge graphs and the representation of shape appearance. To address these problems; we propose an improved generative design approach based on virtual-node based continuous Coordinate Graph Grammar (vcCGG). This approach defines a new type of grammatical rule named node transformation rules to convert nodes into shapes with node transformation applications. By combining node transformation applications and L-applications in vcCGG; we can generate a node-edge graph as the structure of the pattern through L-applications; and then draw the shape outline; next adjust the positions of these shapes; thus relating abstract structures and the physical layouts of visual languages. At the end of the paper; we provide an example application of this approach: generating an illustration from Emma Talbot using a combination of node transformation applications and L-applications. © 2024 Institute of Information Technology; Warsaw University of Life Sciences - SGGW. All rights reserved;

D O I：

10.22630/MGV.2024.33.1.1

中图分类号：

学科分类号：

摘要：

引用

页码：3 / 20