HIGHQUALITY LOW LIGHT IMAGEENHANCEMENT METHOD

Abstract

Over the past decade, vision-based vehicle detection techniques for road safety improvement have gained an increasing amount of attention. Unfortunately, the techniques suffer from robustness due to huge variability in vehicle shape (particularly for motorcycles), cluttered environment, various illumination conditions, and driving behaviour. In this project, we provide on-road vision-based vehicle detection and tracking systems for collision avoidance systems (CASs). This project is structured based on a vehicle detection process starting from sensor selection to vehicle detection and tracking. Techniques in each process/step are reviewed and analysed individually. Two main contributions in this project are the following: insights on motorcycle detection techniques and the sensor comparison in terms of cost and range parameters. Finally, the project provides an optimal choice with a low cost and reliable CAS design in vehicle industries.