A novel approach in real-time vehicle detection and tracking using Raspberry Pi

Abstract

Real-time vehicle detection, tracking and counting of vehicles is of great interest for researchers and is a need of the society in general for comfortable, smooth and safe movements of vehicles in cities. We propose a video image processing algorithm which detects, tracks and finds the number of vehicles on a road. We convert RGB video frame to HSV color domain, which helps in differentiating the colors of the vehicles more absolutely. The noise is removed from each frame. Detection of the vehicles is purely carried on color features of the vehicles. Vehicle tracking is done using Kalman filter with the data association. The number of vehicles running in a video or in a particular lane is determined. We propose a novel idea to detect, track and count the vehicles on a road and it has been implemented on Raspberry Pi 3 using OpenCV and C++. We have compared the results of the proposed method with that of rear-view vehicle detection and tracking method (Bin et al., 2014) and morphological operation method (Zezhong et al., 2013), and found that the proposed algorithm is more effective in terms of accuracy of vehicle detection and cost.