A simple and available system for measuring and evaluating cracks on road pavements using an action camera

Abstract

This study proposes a simple and useful system for measuring and evaluating cracks on road pavements, by updating the same type of system developed in our previous research. In the present system, an action camera (Hero10) is employed, since it can work for more than one hour with a battery and save images and GSP data simultaneously in the memory inside. With some auxiliary devices, it can easily be attached on the roof of a car and capture the same area of road pavements by adjusting those devices. The recorded images are segmentated by an advanced neural network Deeplab v3+, in order to distinguish asphalt pavements from the other objects. Then, each segmentated image is divided into small blocks and they are classified into eight categories according to the state of cracks by a well-known neural network ResNet-18. Finally, crack rates of the images are computed from the results of the classification with new step-wise weights and they are visualized as color contour on a map.