Paper
12 January 2023 Road crack recognition based on object detection
Zhe Liu
Author Affiliations +
Proceedings Volume 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022); 1250906 (2023) https://doi.org/10.1117/12.2656013
Event: Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 2022, Guangzhou, China
Abstract
At present, road crack has become the main threatening factor affecting highway quality. The traditional manual detection method has low efficiency and produces larger errors. Aiming at this problem, this paper presents an improved object detection algorithm based on YOLOv5s network, fused with SE attention mechanism, which strengthens the important characteristic of the fractures of the target and suppresses general characteristics. Finally, we use the accuracy and recall rate as the evaluated parameters. Compared with the original network, the result has improved significantly, which greatly reduce the probability of crack leak fault detection. The location and type of cracks are marked out in the test results of this model, which effectively replaces the traditional manual detection method and optimizes the efficiency of road crack identification. After optimization, the lightweight network can be deployed on various mobile terminal platforms, making full use of the platform computing power, which owns high speed of identification and high precision, and has broad application prospects.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhe Liu "Road crack recognition based on object detection", Proc. SPIE 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 1250906 (12 January 2023); https://doi.org/10.1117/12.2656013
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KEYWORDS
Detection and tracking algorithms

Roads

Target detection

Data modeling

Feature extraction

Network architectures

Object recognition

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