Heavy-Vehicle Detection Using SVM and HOG Features - Sowmya, V; Radha, R (International Journal of Computer Sciences and Engineering, 2025)
Traffic monitoring is important in every country to cope up with the increasing population. Tracking and vehicle monitoring is always a challenging task as they are used for surveillance control and traffic planning. In earlier method, the detection of vehicles is classified using Artificial Neural Network with Histograms of Oriented Gradients. The major challenge due to advent of computer is to choose appropriate algorithms for real time dataset. Therefore, the entire work in this study is carried out by using Python with OpenCV method. A vehicle detection and classification algorithm that works in real time is proposed in this work. Further, the heavy vehicles detection is classified using the Support Vector Machine with a new set of features, Histograms of Oriented Gradients. The results show that the proposed method with Support Vector Machine training parameters is better than earlier method.