A Study on Traffic Parameter Extraction from Instant Image at Night via Image Processing

With the development of ITS, the Traffic Monitoring System is more and more important. Between the many kinds of the vehicle detectors, the computer vision-based vehicle detector has more excellence than other, because that it can obtain more traffic parameters. The processes of daytime image and night image are very different. So we wish to build up a vision-based vehicle detector aimed at the night vehicle flow image.
In this study, we focus on how to extract traffic parameter from instant images at night via image processing. We use the roadside CCTV to capture the image and transmit it through Ethernet. And the image processing procedure includes image pre-processing, background building, morphology processing, camera calibration, sampling tracking, traffic parameter extraction. Before this system start to work, the administrator can set the land line, the image collecting area, and the vehicle flow counter depending on the image circumstances. Hence we can deal with more situations and make the technique more elastic.
Because the night image has more problems than daytime image and deeply influenced by the illumination so we should overcome and adjust more difficulties. Then we establish a platform and use friendly user interface; thus people can operate it easily. And this real-time networked image detector can be used to process the online CCTV image.
Besides, the experimental result shows that we can obtain the vehicle volumes, velocity, occupancy, and etc. And the accurate rate of the vehicle volume can achieve 90%. And the velocity also has enough reliability. The study gives some conclusions and discussions in the end.