Traffic flow statistic and violation detection method based on surveillance video processing

Abstract

The invention discloses a traffic flow statistic and violation detection method based on surveillance video processing. The method comprises the steps of obtaining a video source, reading a frame of image, judging if the current frame is a first frame, utilizing difference information of corresponding pixel points of the current frame and the previous frame to update foreground and background images if the current frame is not the first frame, utilizing the foreground and background images to extract an interest area MASK of the current frame, calculating integral images and integrated square images of the current frame, detecting in the interest area MASK of the current frame if a plate number target exists according to the obtained integral images and integrated square images of the current frame and utilizing an Adaboost algorithm, storing position information of the detected plate number target in a list TmpList, judging if the temporary target list TmpList is empty, judging if a tracking target sequence Track-List is empty if the temporary target list TmpList is empty, and adding the detected target in an ObjList into the Track-List if the tracking target sequence Track-List is empty. By means of the method, crossing traffic flow can be counted precisely, and if a vehicle target breaks the rule is judged combining indication of traffic signal lamps.

Description

technical field [0001] The invention belongs to the fields of image pattern recognition, video target tracking, intelligent video monitoring and intelligent transportation, and more specifically relates to a method for traffic statistics and violation detection based on monitoring video processing. Background technique [0002] Traffic flow is an indispensable and important data for traffic management and regulation. The traffic flow statistics can reflect real-time traffic conditions, which is convenient for traffic managers to regulate and control, and at the same time provides important reference information for residents to travel. More importantly, the traffic flow can reflect the load situation of each road section, providing an important basis for urban planners. In some special occasions such as railway stations, near airports, and some large gathering places, traffic flow statistics technology has important security significance. [0003] The intelligent detection...

AI Technical Summary

Problems solved by technology

Since the calculation is iterative, the error rate of tracking will increase during the iterative process, resulting in errors such as tracking offset and missing targets.

Moreover, most tracking algorithms have a large amount of calculation, and the time consumption exceeds the limit of real-time processing.

Images