Design and development of image processing algorithms for qualitative road traffic data analysis

• Main Author: Guo, Yongsheng.
• Other Authors: Mohammed Yakoob Siyal
• Format: Final Year Project
• Language: English
• Published: 2011
• Subjects: DRNTU::Engineering::Electrical and electronic engineering
• Online Access: http://hdl.handle.net/10356/44931
• Institution: Nanyang Technological University

Road traffic data is a vital tool for traffic engineers in optimizing the efficiency and capacity of any modern transport system. The project aspires to develop a real time traffic analysis system for monitoring traffic flow, and collecting statistical data of traffic analysis. In this project, various algorithms for traffic data analysis were researched and implemented. The system used the window-based approach, and integrated five segmentation techniques such as background difference, inter-frame difference, binary image conversion, quadtree decomposition and edge detection. The qualitative of traffic data analysis such as identify the type of vehicles, detection of the queue, and status of the traffic, which was investigated under the diverse weather conditions. On the whole, the analysis for dry weather condition achieved a more reliable reading than for wet weather condition. The analysis has gave a better overview on factors influencing the qualitative road traffic data analysis and also determinate the most efficient image segmentation technique. Further improvement may include rain removal algorithm and background updating. Modification of the image processing algorithms could be taken to increase the quality and reliability.