An automatic auditing method for illegal bus lane occupation based on deep learning

Abstract

The invention discloses an automatic auditing system for illegal bus lane occupation based on deep learning, and the method comprises the following steps: employing a bayonet camera to carry out the photographing and evidence collection of a target vehicle illegally occupying a bus lane, the evidence collection information comprising n frames (n>=1) of evidence graphs and the license plate numberinformation of the target vehicle; utilizing a yolo-V2 vehicle detection model to detect all vehicles in n frames of images, adopting a caffe-ssd model to detect a license plate area of the all the detected vehicles, and identifying a license plate number by using an lstm + ctc model; comparing the license plate numbers with the edited distance of a given license plate, and applying GoogLenet Inception-V2 network based vehicle re-identification algorithm to respectively position the position of a target vehicle in the n frames of images; segmenting an image bus lane area by using a deeplab-V2segmentation algorithm, and judging whether a target vehicle occupies a bus lane by calculating the ratio of the intersection of the target vehicle detection frame and the bus lane area to the targetvehicle detection frame; and identifying the type of the target vehicle by applying a vehicle classification network based on ResNet18, and finally judging whether the target vehicle illegally occupies the bus lane according to the type information of the target vehicle and the condition of occupying the bus lane. According to the invention, the police is saved, the illegal auditing efficiency andaccuracy are improved, and the auditing fairness is ensured.

Description

technical field [0001] The invention relates to the fields of intelligent image recognition such as target detection and scene segmentation, and in particular to a method and system for automatic review of illegally occupied bus lanes based on deep learning. Background technique [0002] In recent years, the continuous and rapid growth of domestic car ownership has brought severe challenges to road traffic safety, and the traffic department's illegal review work is therefore facing enormous pressure. As an important part of the review of traffic violations, the review of violations of illegally occupying bus lanes is related to the efficiency and safety of public transportation, and occupies a large workload of violation reviews. The existing verification method for illegally occupying bus lanes still mainly adopts the manual verification method, and the existing problems include high labor cost, low efficiency, audit fatigue and personnel subjectivity affecting the fairness...

AI Technical Summary

Problems solved by technology

The existing verification methods for illegally occupying bus lanes still mainly use manual verification methods, and the existing problems include high labor costs, low efficiency, audit fatigue, and personnel subjectivity that affect the fairness and impartiality of the audit.

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