Impact of Image Preprocessing and Crack Type Distribution on YOLOv8-Based Road Crack Detection

Impact of Image Preprocessing and Crack Type Distribution on YOLOv8-Based Road Crack Detection

Road crack detection is crucial for ensuring pavement safety and optimizing maintenance strategies. This study investigated the impact of image preprocessing methods and dataset balance on the performance of YOLOv8s-based crack detection. Four datasets (CFD, Crack500, CrackTree200, and CrackVariety)...

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Bibliographic Details
Main Authors: Luxin Fan, Saihong Tang, Mohd Khairol Anuar b. Mohd Ariffin, Mohd Idris Shah Ismail, Xinming Wang
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Sensors
Subjects:
YOLOv8
crack detection
image preprocessing
deep learning
dataset balancing
pavement inspection
Online Access:https://www.mdpi.com/1424-8220/25/7/2180
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