Automatic analysis of architectural floor plans based on deep learning and morphology

Jingyi Shen; Ying Wang; Tianlin Liang; Xiangyang Gong

doi:10.1117/12.2640387

1 August 2022 Automatic analysis of architectural floor plans based on deep learning and morphology

Jingyi Shen, Ying Wang, Tianlin Liang, Xiangyang Gong

Proceedings Volume 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022); 122570Y (2022) https://doi.org/10.1117/12.2640387
Event: 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 2022, Guangzhou, China

Abstract

In the context of construction engineering, the classification and calculation of the amount of decoration has become the main problem. The structure of engineering drawings is complex and the drawing standards are not unified. This paper proposed a structure extraction algorithm to filter interference lines, extract wall structures and divide spatial regions through image morphology processing based on the image features of floor plan. Based on the target detection algorithm, the drawing scale detection and recognition are realized, and the spatial area calculation is completed through the coordinate system transformation. The results are evaluated by the evaluation standard of graph recognition performance and annotation verification set. The algorithm proposed in this paper is superior to other algorithms in spatial structure analysis, and can effectively analyze and calculate the spatial structure of floor plan in architectural engineering scenes.

Citation Download Citation

Jingyi Shen, Ying Wang, Tianlin Liang, and Xiangyang Gong "Automatic analysis of architectural floor plans based on deep learning and morphology", Proc. SPIE 12257, 4th International Conference on Information Science, Electrical, and Automation Engineering (ISEAE 2022), 122570Y (1 August 2022); https://doi.org/10.1117/12.2640387

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available