Abstract
Engineering drawings play an important role in fields such as architecture, industrial engineering, and electric engineering, within which tables contain essential data and structures. However, most engineering drawings exist in the form of scanned PDFs or images, which is inconvenient for data management and storage, especially for table information. Also, many industries are in urgent need of data management software for engineering drawings to improve the degree of digital preservation and management. To this end, a software, ED Manager which is based on the fusion of deep learning and traditional image processing, is presented to detect the position and structure of the table, split and recognize characters, and reconstruct the table in a digital form. Further, we extract crucial information and develop a user interface and database to construct a comprehensive model that fits most engineering drawings. Our software can accurately locate tables for various complex drawings, extract structured information from tables, and build a better data management software for engineering drawings.
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Acknowledgements
This work was partially funded by the National Key Research and Development Plan of China (No. 2018AAA0101000) and the National Natural Science Foundation of China under grant 62076028.
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Yang, H., Du, Y., Guo, J., Wei, S., Ma, H. (2022). Engineering Drawing Manager: A Smart Data Extractor and Management Software. In: Liu, H., et al. Intelligent Robotics and Applications. ICIRA 2022. Lecture Notes in Computer Science(), vol 13458. Springer, Cham. https://doi.org/10.1007/978-3-031-13841-6_22
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DOI: https://doi.org/10.1007/978-3-031-13841-6_22
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