Line art extraction of Chinese building structure based on ControlNet model

Fan Wu; Junjie Cheng; Shuchang Xu

doi:10.1117/12.3057818

13 February 2025 Line art extraction of Chinese building structure based on ControlNet model

Fan Wu, Junjie Cheng, Shuchang Xu

Author Affiliations +

Proceedings Volume 13539, Sixteenth International Conference on Graphics and Image Processing (ICGIP 2024); 135391H (2025) https://doi.org/10.1117/12.3057818
Event: Sixteenth International Conference on Graphics and Image Processing (ICGIP 2024), 2024, Nanjing, China

Abstract

Drawing architectural plan is a crucial step in the preservation of ancient Chinese building. This process is often time-consuming and typically carried out by skilled human. This paper presents a method for automatically extracting line art of building structures, which significantly enhances the efficiency of creating architectural plans. We first introduce a dataset of images featuring Huizhou-style ancient buildings. Each building image is then segmented into various components to identify the main structure. The SUPIR model can optionally be employed to enhance the component images with super-resolution. Moreover, we developed a split-and regroup algorithm specifically for the eave's component, which often presents challenges such as broken, tilted, or occluded roof tiles. Finally, we trained a line art extraction model using ControlNet and LoRA. The experiments demonstrate that our method yields more detailed images than existing algorithms.

(2025) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Fan Wu, Junjie Cheng, and Shuchang Xu "Line art extraction of Chinese building structure based on ControlNet model", Proc. SPIE 13539, Sixteenth International Conference on Graphics and Image Processing (ICGIP 2024), 135391H (13 February 2025); https://doi.org/10.1117/12.3057818

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