Video-Based Automated System for Pavement Surface Quality Monitoring

Abstract

Nowadays, an important task is to evaluate the pavement condition, in order to perform necessary works for keeping the road safe. Performing such kind of surveys and calculations on the roads only by humans is ineffective not only concerning time but it also requires more costs and may be unsafe for pavement condition inspectors. In this paper we introduce an automated monitoring system, which can classify cracks and artifacts from pavement video images and illustrate the processed images results during image acquisition. Firstly, a threshold value is counted using the image histogram. Then, image processing operations are applied, namely binarization and segmentation on each frame. Afterwards, the image is filtered from small segments which don't contain crack information. Finally, the defect percent of each frame is counted and displayed on the graph real-time, where areas with cracks are distinguishable for pavement management operators. This information is helpful for pavement condition rating. Experimental data were from real road images in Armenia.