Next Article in Journal / Special Issue
Toward the Development of Load Transfer Efficiency Evaluation of Rigid Pavements by a Rolling Wheel Deflectometer
Previous Article in Journal / Special Issue
Fraction Factorial Design of a Novel Semi-Transparent Layer for Applications on Solar Roads
Open AccessArticle

Exploiting Low-Cost 3D Imagery for the Purposes of Detecting and Analyzing Pavement Distresses

DIING—Department of Engineering, University of Palermo, Viale delle Scienze ed.8, 90128 Palermo, Italy
Author to whom correspondence should be addressed.
Infrastructures 2020, 5(1), 6;
Received: 28 November 2019 / Revised: 8 January 2020 / Accepted: 11 January 2020 / Published: 14 January 2020
Road pavement conditions have significant impacts on safety, travel times, costs, and environmental effects. It is the responsibility of road agencies to ensure these conditions are kept in an acceptable state. To this end, agencies are tasked with implementing pavement management systems (PMSs) which effectively allocate resources towards maintenance and rehabilitation. These systems, however, require accurate data. Currently, most agencies rely on manual distress surveys and as a result, there is significant research into quick and low-cost pavement distress identification methods. Recent proposals have included the use of structure-from-motion techniques based on datasets from unmanned aerial vehicles (UAVs) and cameras, producing accurate 3D models and associated point clouds. The challenge with these datasets is then identifying and describing distresses. This paper focuses on utilizing images of pavement distresses in the city of Palermo, Italy produced by mobile phone cameras. The work aims at assessing the accuracy of using mobile phones for these surveys and also identifying strategies to segment generated 3D imagery by considering the use of algorithms for 3D Image segmentation to detect shapes from point clouds to enable measurement of physical parameters and severity assessment. Case studies are considered for pavement distresses defined by the measurement of the area affected such as different types of cracking and depressions. The use of mobile phones and the identification of these patterns on the 3D models provide further steps towards low-cost data acquisition and analysis for a PMS. View Full-Text
Keywords: road pavement distress; low-cost technologies; 3D models; structure-from-motion road pavement distress; low-cost technologies; 3D models; structure-from-motion
Show Figures

Graphical abstract

MDPI and ACS Style

Roberts, R.; Inzerillo, L.; Di Mino, G. Exploiting Low-Cost 3D Imagery for the Purposes of Detecting and Analyzing Pavement Distresses. Infrastructures 2020, 5, 6.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

Back to TopTop