Concrete crack segmentation method and device based on YOLOv4 target detection model and tubular flow field algorithm

Abstract

The invention discloses a concrete crack segmentation method and device based on a YOLOv4 target detection model and a tubular flow field algorithm, and belongs to the technical field of concrete structure damage detection, and the method comprises the steps: obtaining a crack picture, marking a label on the picture, and forming a crack database; inputting the database into a YOLOv4 model, and training a target detection model for the crack; carrying out sparse training on the trained YOLOv4 model, and then carrying out pruning to obtain a YOLOv4-P model; and inputting a to-be-detected image into the YOLOv4-P model for detection, cutting the detected crack, reinforcing the cut crack image by using a contrast-limited adaptive histogram equalization algorithm, and inputting the reinforced crack image into a tubular flow field algorithm for crack segmentation. Compared with a semantic segmentation model, the method and device have the advantages that the workload of image annotation is greatly reduced, real-time performance is achieved, the detection result is accurate, and practical engineering significance is achieved.

Description

technical field [0001] The invention belongs to the technical field of concrete structure damage detection, and in particular relates to a concrete crack segmentation method and device based on a YOLOv4 target detection model and a tubular flow field algorithm. Background technique [0002] Cracks in the surface of concrete structures are a harbinger and a common symptom of infrastructure degradation. Regular crack inspection and repair play a very important role in the maintenance and operation of infrastructure. Through early and timely assessment and investigation, certain safety measures can be taken to prevent further damage and failure, and effective data support can also be provided for structural health assessment. [0003] It is the early mainstream that maintenance personnel use some special testing equipment for testing. This method has obvious defects in efficiency, cost and accuracy. Since then, many crack detection methods based on contact or embedded sensors...

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Problems solved by technology

[0007] The purpose of the embodiment of the present invention is to provide a concrete crack segmentation method and device based on the YOLOv4 target detection model and the tubular flow field algorithm to solve various defects that only use a single image processing technology, target detection algorithm and semantic segmentation algorithm at present

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