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DOI: 10.14569/IJACSA.2025.0160229
PDF

Integrating Artificial Intelligence to Automate Pattern Making for Personalized Garment Design

Author 1: Muyan Han

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 16 Issue 2, 2025.

  • Abstract and Keywords
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Abstract: This paper introduces an innovative AI-assisted pattern construction tool that leverages machine learning models to revolutionize pattern generation in garment design. The proposed system automatically generates patterns from 3D body scans, which are converted into 3D shell meshes and subsequently flattened into 2D patterns using advanced data augmentation techniques and CAD flattening algorithms. This approach eliminates the need for expertise in traditional pattern-making, enabling seamless transformation of 3D models into realistic garment patterns. The tool accommodates various garment styles, including fitted, standard fit, and relaxed fit, while also enabling high levels of personalization by adapting patterns to individual body dimensions. Through its AI-driven automation and user-friendly interface, this plug-in enhances accessibility, allowing individuals without conventional design skills to create customized apparel efficiently.

Keywords: Machine learning models; pattern generation; AI-assisted pattern construction; data augmentation techniques; CAD flattening

Muyan Han. “Integrating Artificial Intelligence to Automate Pattern Making for Personalized Garment Design”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.2 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0160229

@article{Han2025,
title = {Integrating Artificial Intelligence to Automate Pattern Making for Personalized Garment Design},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160229},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160229},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {2},
author = {Muyan Han}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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