Title: An automatic moving vehicle detection system based on hypothesis generation and verification in a traffic surveillance system

Authors: J.A. Smitha; N. Rajkumar

Addresses: Department of CSE, Sri Sairam College of Engineering, Bangalore, Karnataka, India ' Department of CSE, KGiSL Institute of Technology, Coimbatore, Tamil Nadu, India

Abstract: An intelligent transportation system has a major topic called traffic surveillance. In a complex urban Traffic Surveillance System (TSS), booming of vehicle detection and tracking is a dilemma. To overcome the problem, a two stage approach for moving vehicle detection system is proposed in this paper. The proposed system mainly consists of two stages namely, Hypothesis Generation (HG) and Hypothesis Verification (HV). At the first step, hypotheses are generated by shadows beneath the vehicles is darker than the road region concept. In the second step a generated hypothesis is verified as correct or not using Optimal Artificial Neural Network (OANN). The weights corresponding ANN is optimally selected using Grasshopper Optimisation Algorithm (GOA). Through experimental results, it is shown that the proposed moving vehicle detection system has better accuracy compared to other methods.

Keywords: traffic surveillance system; moving vehicle detection; tracking; hypothesis generation; hypothesis verification; feedforward neural network; grasshopper optimisation algorithm.

DOI: 10.1504/IJVICS.2023.131581

International Journal of Vehicle Information and Communication Systems, 2023 Vol.8 No.1/2, pp.170 - 188

Received: 05 Jul 2019
Accepted: 13 Oct 2019
Published online: 20 Jun 2023 *