Research on Frame and Table Recognition Based on CAD Drawings

In the process of drawing architectural drawings with AutoCAD software, enterprises will produce a large number of CAD drawings in DWG format. The tables of these CAD drawings contain rich textual information. These text information constitute the key data base of enterprise systematic management drawings. At present, the systematic management of drawing data needs to collect these sheet data, but the sheet data collection mainly depends on manual input, which leads to high error rate of data collection, huge workload, long compilation cycle and low work efficiency. The purpose of this paper is to discuss how to deal with these tables efficiently. Firstly, based on Revit secondary development, the frame recognition algorithm is proposed, which confirms the inner and outer frame by finding the largest rectangle and the second largest rectangle. In addition, the Teigha class library is used to extract text, so as to extract key data, so as to promote the collection, reuse and systematic management of product data. Through the processing of drawing frames and forms, it lays a good foundation for subsequent component identification. The method proposed in this paper has strong versatility and adaptability, and can basically realize the recognition of CAD drawing frame and form, and extract form text, and achieve higher accuracy and efficiency.

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Publication Details

Published
2024-11-01
DOI
https://doi.org/10.1109/cac63892.2024.10865673
Primary Topic
Industrial Vision Systems and Defect Detection
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article
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article

Research on Frame and Table Recognition Based on CAD Drawings

Yongwei Miao, Hui Zhong
Industrial Vision Systems and Defect Detection
article

Research on Frame and Table Recognition Based on CAD Drawings

Yongwei Miao, Hui Zhong
article en

Abstract

In the process of drawing architectural drawings with AutoCAD software, enterprises will produce a large number of CAD drawings in DWG format. The tables of these CAD drawings contain rich textual information. These text information constitute the key data base of enterprise systematic management drawings. At present, the systematic management of drawing data needs to collect these sheet data, but the sheet data collection mainly depends on manual input, which leads to high error rate of data collection, huge workload, long compilation cycle and low work efficiency. The purpose of this paper is to discuss how to deal with these tables efficiently. Firstly, based on Revit secondary development, the frame recognition algorithm is proposed, which confirms the inner and outer frame by finding the largest rectangle and the second largest rectangle. In addition, the Teigha class library is used to extract text, so as to extract key data, so as to promote the collection, reuse and systematic management of product data. Through the processing of drawing frames and forms, it lays a good foundation for subsequent component identification. The method proposed in this paper has strong versatility and adaptability, and can basically realize the recognition of CAD drawing frame and form, and extract form text, and achieve higher accuracy and efficiency.

Shenyang Jianzhu University (CN)
Openalex Percentile: Top 60%
Industrial Vision Systems and Defect Detection
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