Reconstructing BIM from 2D structural drawings for existing buildings

Reconstructing building information models (BIMs) based on 2D drawings is an effective way to realize digital management of existing buildings. However, current image-based methods require much time as well as professional knowledge to manually design and extract features from drawing images. Moreover, the quality of generated BIM cannot be guaranteed when dealing with the drawings drawn under different design standards and drawing conventions. In this study, a novel hybrid method, integrating technologies like image processing, deep learning and optical character recognition (OCR), is proposed to extract the information of objects from the images of structural drawings (i.e. grids, columns and beams), and generate industry foundation classes (IFC) BIM for existing buildings. Experiments are carried out to verify the performance of the proposed method and the results demonstrate the feasibility and reliability of the method. Several accuracy-influencing factors are also analyzed and discussed in this paper.

Automated summary

A novel hybrid method integrating technologies such as image processing, deep learning, and optical character recognition is proposed to extract object information from structural drawings and generate BIM for existing buildings. Experiments verify the feasibility and reliability of the method, while also analyzing several factors influencing accuracy.