Automatic generation of parametric patterns from grading patterns using artificial intelligence
International Journal of Clothing Science and Technology
ISSN: 0955-6222
Article publication date: 18 September 2023
Issue publication date: 31 October 2023
Abstract
Purpose
This study aims to automate the process of converting grading patterns into parametric patterns using artificial intelligence and to objectively evaluate the fitness of the converted patterns.
Design/methodology/approach
The developed system consists of a user interface that defines input data by importing multi-size grading patterns, an artificial neural network that learns the relationship between human body size and pattern geometry, and a module that converts training results into parametric patterns. In order to evaluate the fitness of the generated pattern, an objective fitting evaluation method using drape simulation was developed.
Findings
The body sizes of the wearer were input to the converted parametric pattern to generate a customized pattern. Resulting pattern showed a better fit than the grading pattern on the off-average body model.
Research limitations/implications
In this study, a method has been developed that enables the users with minimal pattern drafting knowledge to convert grading patterns into parametric patterns using artificial intelligence and drape simulation. The human body's symmetry and the physical properties of fabric were not considered.
Originality/value
The system developed in this study requires less data compared to existing methods that attempt to design clothing patterns with machine learning. In addition, it was possible to evaluate pattern fitness on various body models through drape simulation based fit evaluation process for the first time.
Keywords
Citation
Oh, J. and Kim, S. (2023), "Automatic generation of parametric patterns from grading patterns using artificial intelligence", International Journal of Clothing Science and Technology, Vol. 35 No. 6, pp. 889-903. https://doi.org/10.1108/IJCST-07-2022-0102
Publisher
:Emerald Publishing Limited
Copyright © 2023, Emerald Publishing Limited