A Vehicle Flow Counting Method Based on Mixed Gaussian Model

Abstract

The invention discloses a traffic flow counting method based on a mixed Gaussian model, comprising the following steps: step 1, setting a detection area on the lane of the highway monitoring area; step 2, collecting video data in the detection area and performing preprocessing Step 3, using the mixed Gaussian model to carry out background modeling, separating background pixels from the original image; Step 4, extracting the moving target from the surveillance video image; Step 5, recording the track information of the moving target, thereby identifying the vehicle information, and Marking; step 6, tracking and counting the marked vehicles, thereby calculating the traffic flow. The invention uses the advantages of the Gaussian mixed model to carry out background modeling on the detection zone, and extracts the moving target through the background difference method, thereby realizing the multi-lane traffic flow detection, which can be applied to complex scenes, has high detection accuracy, good real-time performance, and has practical value .

Description

technical field [0001] The invention relates to the technical field of security monitoring, and more specifically, the invention relates to a method for counting traffic flow based on a mixed Gaussian model. Background technique [0002] With the rapid development of the modern economy, road transport has become an important means of transport in the transport industry. In order to ensure smooth traffic and driving safety, thereby improving environmental quality, the collection of traffic information is the basis of intelligent transportation systems, and the traffic flow of highways is an important part of intelligent transportation systems, so the detection of traffic flow is particularly important. [0003] The existing traffic flow detection methods in current traffic information are mainly divided into three parts: extracting moving objects from image sequences, identifying the extracted objects and counting the traffic flow. [0004] The traditional method for extract...

AI Technical Summary

Problems solved by technology

[0004] The traditional method for extracting moving objects is the background subtraction method, which uses the weighted average method to update the background, but it is easy to detect the background exposed area as the foreground, that is, the current background still has the moving object information of the previous frame, but the moving object has already disappeared at this time. If it is not in this area, there will be a "shadow" phenomenon, and the noise processing effect is not good in complex scenes such as tree branches swinging, the adaptability to the environment is poor, and the update effect is not ideal, resulting in incomplete extraction of moving vehicles, which affects the vehicle Detection accuracy

Images