Image Features Selection Based on Computer Vision Techniques to Detect Potholes for Intelligent Transport System

Abstract

Computer vision is an emerging area for image processing that is well utilized in the field of Intelligent Transport Systems. There are various techniques used to increase the efficiency of ITS such as GPS, radar-based, sensors utilization, more importantly, through Surveillance, etc. It found that costs for all techniques were high to implement on a large scale. The need of the hour is to have efficient techniques or models that will help to reduce the cost of ITS. Computer vision is a field that provides cutting-edge solutions in ITS. This paper explores the image features selection based on computer vision techniques to detect the potholes on the road. It will help to improve the Intelligent Transport System for a smart city. In this paper, the authors will discuss the computer vision techniques like Corner Detection-Harris, HOG, and Feature Extraction through FAST.