Deep learning vehicle counting method based on road surface extraction and segmentation

Abstract

The invention discloses a deep learning vehicle counting method based on road surface extraction and segmentation. The method specifically comprises: collecting video images of a road by using a camera; adopting a digital image processing method to acquire a road surface area and adopting a segmentation strategy to segment a road surface into a near end part and a far end part; sending the segmented road surface area into a deep learning network to detect a vehicle target, carrying out continuous tracking according to a detection result to obtain a vehicle two-dimensional trajectory, and counting the flow of different types of vehicles in a certain road direction by using the vehicle two-dimensional trajectory to achieve the purpose of vehicle counting. According to the method, the detection precision of small vehicles far away from the road surface is high, and a data basis is provided for accurate vehicle counting. The method can be applied to various traffic scenes, has high stability and counting precision, can effectively and accurately detect and continuously track vehicles in a road range in an image visual field so as to realize vehicle counting, and has a wide applicationprospect.

Description

technical field [0001] The invention belongs to the technical field of video detection, and in particular relates to a deep learning vehicle counting method based on road surface extraction and segmentation. Background technique [0002] The intelligent supervision of highways has attracted more and more attention in the field of intelligent transportation. my country's economy is in a stage of rapid development, and the increasing number of vehicles has brought serious traffic congestion and reduced the traffic capacity of the road. Therefore, it is very necessary to use newer technological methods to intelligently manage roads and provide road traffic flow metadata. Vehicle detection and traffic statistics are carried out on the road range monitored by surveillance cameras, so as to provide data for traffic management departments and other related industries, and achieve the purpose of intelligent highway management and control. [0003] The use of surveillance video for...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the defects and deficiencies in the prior art, the present invention provides a deep learning vehicle counting method based on road surface extraction and segmentation, which solves the problem that the current vehicle detection method based on surveillance video has low detection accuracy for vehicles, especially for road surface There are problems such as undetectable small vehicles in the distance

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