Due to the rapid growth of vehicles and traffic accidents caused by road pavement defects, road safety has become a pressing concern worldwide. For this reason, Countries and Federal States have started focusing their resources on the analysis of civil infrastructures to assess their safety and serviceability. The analyses are performed by specialized teams of inspectors and structural engineers who manually inspect road infrastructures and provide detailed reports about the detected pavement distresses and their magnitudes. This work aims at providing a new system able to detect the framed distress using solely the computational resources provided by a mobile device To reach this goal, an automatic pavement distress recognition system based on the OpenCV library is developed and embedded in a mobile application, enabling the recognition of three common pavement distresses: Pothole, Longitudinal-Transversal Cracks, and Fatigue Cracks. Our method, tested on several Android mobile platforms, is able recognize the pavement distresses of interest reaching more than 0.7 of Precision, Recall, Accuracy, and F-Measure. This application promises to improve the on-site work of inspectors by decreasing the time required to perform inspections while ensuring, at the same time, a higher level of accuracy.
Tedeschi, A., Benedetto, F. (2017). A real-time automatic pavement crack and pothole recognition system for mobile Android-based devices. ADVANCED ENGINEERING INFORMATICS, 32, 11-25 [10.1016/j.aei.2016.12.004].
A real-time automatic pavement crack and pothole recognition system for mobile Android-based devices
Benedetto, F
2017-01-01
Abstract
Due to the rapid growth of vehicles and traffic accidents caused by road pavement defects, road safety has become a pressing concern worldwide. For this reason, Countries and Federal States have started focusing their resources on the analysis of civil infrastructures to assess their safety and serviceability. The analyses are performed by specialized teams of inspectors and structural engineers who manually inspect road infrastructures and provide detailed reports about the detected pavement distresses and their magnitudes. This work aims at providing a new system able to detect the framed distress using solely the computational resources provided by a mobile device To reach this goal, an automatic pavement distress recognition system based on the OpenCV library is developed and embedded in a mobile application, enabling the recognition of three common pavement distresses: Pothole, Longitudinal-Transversal Cracks, and Fatigue Cracks. Our method, tested on several Android mobile platforms, is able recognize the pavement distresses of interest reaching more than 0.7 of Precision, Recall, Accuracy, and F-Measure. This application promises to improve the on-site work of inspectors by decreasing the time required to perform inspections while ensuring, at the same time, a higher level of accuracy.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.