A method for detecting cracks in building facades by combining 2D images and 3D point clouds

By combining two-dimensional images with three-dimensional point clouds, the accuracy problem of detecting cracks on building facades in complex, highly reflective environments was solved. This method enables precise identification and quantitative assessment of cracks, eliminates false point clouds, and improves the reliability of detection.

CN121883493BActive Publication Date: 2026-06-30ZHEJIANG COLLEGE OF CONSTR +1
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG COLLEGE OF CONSTR
Filing Date
2026-03-19
Publication Date
2026-06-30

AI Technical Summary

Technical Problem

Existing technologies struggle to accurately detect cracks on building facades in complex, highly reflective environments. 3D point cloud data is prone to false point clouds and point cloud expansion, leading to large detection errors and making it difficult to accurately identify crack features.

Method used

A method for detecting cracks in building facades that combines 2D images and 3D point clouds is proposed. This method acquires 3D point cloud data and 2D images of the building facade, converts them into 2D depth images, extracts crack regions, obtains crack region matching pairs based on pixel coordinate coincidence and principal axis similarity, and uses a crack recognition neural network model to determine the 3D coordinates and curvature of the real crack point cloud, thereby obtaining the crack type, width, and depth.

Benefits of technology

Effective elimination of false point clouds improves the accuracy and robustness of crack detection, ensures the authenticity of point cloud data, enables accurate qualitative and quantitative assessment of cracks, and reduces the false detection rate.

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Abstract

This invention relates to the field of image data analysis technology, specifically to a method for detecting cracks in building facades that combines two-dimensional images and three-dimensional point clouds. The method acquires three-dimensional point cloud data and two-dimensional images of the building facade; converts each frame of the three-dimensional point cloud data into a two-dimensional depth image, and extracts crack regions from both the two-dimensional depth image and the two-dimensional image; based on the positional overlap of crack regions between the two-dimensional depth image and the two-dimensional image, obtains crack region matching pairs; based on the overlap of pixel coordinates in the crack region matching pairs, as well as the similarity of principal axis direction and skeleton length, obtains the overall matching degree of the crack region matching pairs; based on the overall matching degree, determines the true crack point cloud, and based on the three-dimensional coordinates and curvature of the true crack point cloud, obtains the crack type, width, and depth. This invention effectively improves the accuracy and robustness of building facade crack detection by accurately acquiring the true crack point cloud.
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