Research On Vehicle Detection And Vehicle Flow Detection Method Based On Video

With the rapid development of the modern economy, keeping traffic and transportation safe and orderly is becoming more and more important; Intelligent Traffic System is being followed. Technology of the vehicle detection is the key to the series of technologies for the intelligent traffic system. Research on the technology for the vehicle detection based on image processing is just the hot of the field. Technological innovations have given rise to different types of traffic detectors. Conventional detectors,for example, inductive loop,detectors using ultrasonic,microwave,or infrared, have been put into use for several decades. Meanwhile,a Promising approach, video-based measurement system, has developed quickly. Since it has many advantages,for instance,wider-area detection and superior flexibility,many research have been done in this field.In recent years, the scholars home and abroad have done extensive research on moving object detection based on video. Traditional methods of vehicle detection include: background difference, temporal difference, and optical flow method and so on. Among these methods, the background difference method has been widely used in moving object detection area because of its little calculation and being able to use background updating technology to implement self-adaptive background updating. This method can precisely segment the moving object from background. However it still has many disadvantages, many improvements have been done according to the need. The temporal difference method adopts the difference based on pixel among two frames or three frames in sequential image sequence. However it can not obtain all characteristic pixels, and bring holes in the moving entity. Due to the great calculation, bad de-noise ability and depending on hardware, the application of optical flow method is restricted.This paper proposes the method that combines background difference and virtual-loop sensor to detect vehicle flow, it takes the self-adaptive background updating method based on moving region into the video image motion detection segmentation technology,and it presents a new vehicle flow detection method based on virtual-loop sensor, which based on the vehicle detection method based on moving region. Setting virtual-loop sensor along the vertical direction of the road to detect vehicle flow. Only the image data within the virtual-loops are processed, so the time cost of calculation is reduced and fast processing speed. From the result of a series experiments, we can see that this method can update the background exactly along with the variance of illumination, fast segment the inside moving target and accurately detect vehicle flow, so this method has quite strong real time quality and robust quality.