Background and inter-frame difference algorithm-based traffic flow and motion state detection method

Abstract

The invention discloses a background and inter-frame difference algorithm-based traffic flow and motion state detection method, which comprises the following steps of: first performing gray processing on a real-time road surface image shot by a high-definition monitoring camera; then performing background differential operation on a group of gray-processed image comprising a plurality of frames to obtain a differential image, extracting vehicle characteristic areas, and calculating a traffic flow area and the ratio of the traffic flow area to a road surface area to obtain traffic flow information; next selecting differential images processed by the steps (1) and (2) at moments K and K+1, and performing inter-frame differential operation to obtain a traffic flow area variation and the ratio of the traffic flow area variation to the road surface area to further obtain traffic flow motion state information; and finally comprehensively analyzing the traffic flow information and the motion state information, encoding different road traffic flow conditions, and predicting a road traffic flow condition. Data support can be provided for intelligent traffic lights, a foundation can be laid for the development of intelligent traffic, and the method has broad application prospect.

Description

technical field [0001] The invention relates to the field of road traffic, in particular to a method for detecting traffic flow and its motion state based on a background and inter-frame difference algorithm. Background technique [0002] With the development of human society, the pressure on road traffic is increasing day by day, and traffic congestion has become one of the most prominent problems in major cities. [0003] At present, the time of traffic lights is fixed, and the time configuration cannot be changed according to the traffic flow in real time. Existing detection of traffic flow includes geomagnetic induction detection, but it is very inconvenient to dig out the road surface during construction; there are also laser and ultrasonic detection, etc., but the functions are very limited and difficult to promote. Now the intersections on the main roads are basically equipped with high-definition surveillance cameras. At the same time, after years of development, ma...

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Problems solved by technology

[0004] At present, machine vision is also used to detect road traffic flow. Wu Lingxiao, Lin Chen, Xu Fuhai, Zhao Xiaojun and others published a vehicle counting method based on background difference in "Automation Technology and Application" 2011,30(10):72-75. However, this method only focuses on the tracking of a single target, but does not detect and analyze the overall situation of the road, which restricts the application of machine vision in road traffic detection

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