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Automatic embroidery texture synthesis for garment design and online display

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Abstract

We introduce an automatic texture synthesis-based framework to convert an arbitrary input image into embroidery style art for garment design and online display. Given an input image and some reference textures, we first extract key embroidery regions from the input image using image segmentation. Each segmented region is single-colored and labeled with a stitch style automatically. We then fill these regions with embroidery reference textures via a stitch-style-based texture synthesis method. For each region, our approach maintains color similarity before and after synthesis, along with stitch style consistency. Compared to existing approaches, our method is able to generate digital embroidery patterns with faithful details automatically. Moreover, it can accept diverse input images effectively, enabling a fast preview of the embroidery patterns synthesized on digital garments interactively, and therefore accelerating the workflow from design to production. We validate our method through extensive experimentation and comparison.

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Acknowledgements

We thank the anonymous reviewers for their constructive comments. Xiaogang Jin was supported by the National Key R&D Program of China (Grant No. 2017YFB1002600), the National Natural Science Foundation of China (Grant No. 61732015), the Ningbo Major Special Projects of the “Science and Technology Innovation 2025” (Grant No. 2020Z007), and the Key Research and Development Program of Zhejiang Province (Grant No. 2018C01090).

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Authors and Affiliations

  1. State Key Lab of CAD&CG, Zhejiang University, Hangzhou, 310058, China

    Xinyang Guan & Xiaogang Jin

  2. Zhejiang Linctex Digital Technology Co. Ltd., Hangzhou, China

    Likang Luo & Chen Liu

  3. Quanzhou Medical College, Quanzhou, China

    Honglin Li

  4. School of Computing, University of Leeds, Leeds, UK

    He Wang

  5. School of Software and Microelectronics, Peking University, Beijing, China

    Su Wang

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  1. Xinyang Guan
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  2. Likang Luo
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  3. Honglin Li
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  4. He Wang
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  5. Chen Liu
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  6. Su Wang
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Correspondence to Xiaogang Jin.

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Guan, X., Luo, L., Li, H. et al. Automatic embroidery texture synthesis for garment design and online display. Vis Comput 37, 2553–2565 (2021). https://doi.org/10.1007/s00371-021-02216-0

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