Image processing system for qualitative road traffic data analysis - Cho Zin Ye Swe (2019)
Increasing numbers of vehicle population has been a major concern for government and traffic engineers. Traffic engineers in modern age are constantly looking for innovative ways to improve and optimize the efficiency and capacity of the modern traffic monitoring system. Vision-Based traffic systems are long been using in current road traffic systems to monitor the traffic flow and road accidents. Extreme weather conditions and huge traffic influx during peak hours are affecting the accuracy of the traffic monitoring system effectiveness. This project main objective is to research and study real time traffic monitoring system by using image processing algorithm and create a comparative analysis of the various results. This project aspires to better the current efficiency and collect variety of data for future possible applications. Vision-Based traffic systems are approached by using the Graphic User Interface (GUI) and Image Processing Toolbox of the MATLAB software. Edge detection, inter-frame difference and background difference were researched for traffic roads of various geographical locations, weather conditions and lighting conditions from different cities Vehicle registration plate recognizing using the OCR characters segmentation, road traffic sign recognizing by HSV colour mapping technique and vehicle counting on different lanes to determine the traffic congestion by using Fuzzy Logic algorithms were tested in the project using MATLAB (GUI). Obtaining quantitative data and comparison of various results were carried out to classify which methods give the more reliable results to apply in solving the real-life traffic problems. This report collects all the experiments and finding from the project and illustrates the GUI application tested during the progress.