Vehicle flow counting method

Abstract

The invention provides a vehicle flow counting method. The method includes the following steps that: step 1, detection regions are arranged at fixed positions on two sides of a lane in a road monitoring region; second step, the video data of the monitoring region are collected, and are preprocessed; third step, a mixed Gaussian model is utilized to perform background modeling, and background pixels are separated from an original image; fourth step, moving targets are extracted from monitoring video images; fifth step, the trajectory information of the moving targets is recorded, and therefore,the information of vehicles can be identified, the vehicles are marked; sixth step, the marked vehicles are tracked and counted, and vehicle flow can be calculated. According to the vehicle flow counting method of the invention, the traffic flow of roads can be monitored in real time, and vehicles on the roads can be accurately and efficiently detected, tracked and counted in real time in an all-around manner. The vehicle flow counting method can be applicable to complex conditions and has high detection accuracy, high real-time performance and important application value.

Description

technical field [0001] The invention belongs to the technical field of security monitoring, in particular to a method for counting traffic flow. 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, traffic flow detection on highways is particularly important. The existing traffic flow detection methods in current traffic are mainly divided into three parts: extracting moving targets from image sequences, identifying the extracted targets and counting vehicles. [0003] The traditional method for extracting moving objects is the background difference method, which uses the weighted average method to update the background, but the update effect is not ideal, resulting in incomplete extraction of moving vehicles, which affects the accuracy of vehicle detection. Contents o...

AI Technical Summary

Problems solved by technology

[0003] The traditional method of extracting moving objects is the background difference method, which uses the weighted average method to update the background. The update effect is not ideal, resulting in incomplete extraction of moving vehicles, which affects the accuracy of vehicle detection.

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