Pothole detection using image surveillance system: A review

Abstract

Recent studies have shown that researchers have proposed various techniques for Pothole detection using data collected from different parts of the world. Automating pothole detection will go a long way in providing safe driving for road users and intelligent transportation systems. This is not only necessary to guarantee safe and adequate performance, but also to adjust to the drivers’ needs, potentiate their acceptability, and ultimately meet drivers’ preferences in bad roads. Machine learning and Object detection algorithms are mainly traditional or deep learning based. Currently, algorithms based on deep learning are widely used in various fields as a mainstream method of object detection. This paper reviewed the various pothole detection systems with different road characteristics and dataset locations. This work was able to highlight various machine learning and object detection techniques that can be applied to pothole detection which has been used in different road characteristics and their corresponding form of dataset as presented by various researchers across the world.