Vehicle type identification method based on machine vision and deep learning

A deep learning and vehicle type technology, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve problems such as high error rate, serious occlusion, overlapping vehicles, etc., improve accuracy and precision, and reduce recognition and detection errors , Good detection effect

Pending Publication Date: 2020-08-07
HANGZHOU DIANZI UNIV
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AI Technical Summary

Problems solved by technology

[0004] However, in the field of intelligent transportation, because some images are collected through the use of vehicle-mounted mobile platforms, the overlapping and occlusion of vehicles

Method used

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  • Vehicle type identification method based on machine vision and deep learning
  • Vehicle type identification method based on machine vision and deep learning
  • Vehicle type identification method based on machine vision and deep learning

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[0049] The following is a detailed description of the system for detecting the type of traffic road vehicles based on machine vision and the accompanying drawings, so as to clearly and completely describe the technical solutions in the embodiments of the present invention.

[0050] In the example of the present invention, a residual yarn detection method based on machine vision is proposed, such as figure 1As shown, in the specific scheme, it can be divided into three steps: image acquisition and preprocessing, yolov3 preliminary detection of targets and classifier re-identification. First, it is necessary to use mobile platforms and industrial cameras to capture images from traffic road scenes, and perform preprocessing such as Gaussian filtering on the collected images. Then send the preprocessed image to the yolov3 target detector and get the preliminary detection frame and confidence, and then decide whether to send it to multiple classifiers for re-prediction by judging t...

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Abstract

The invention discloses a vehicle type identification method based on machine vision and deep learning. At present, most of the vehicle identification fields take images collected by high-altitude cameras as data sets, and images collected by mobile platforms are rarely taken as data sets. If a traditional image recognition technology is used, the requirement for mobile violation evidence obtaining cannot be met. According to the method, firstly, image information of a road automobile is collected through a vehicle-mounted mobile platform, preliminary automobile target detection and recognition are conducted through a yolov3 algorithm in deep learning, and then whether the image information is sent to three classifiers for re-prediction or not is comprehensively judged according to a detection frame and a prediction value threshold value. According to the detection results of the three classifiers and a target detection algorithm result, whether the detection box is subjected to errordetection and deletion or not is determined. Finally, a detection result of the system is updated. The method is suitable for the field of vehicle identification of the vehicle-mounted mobile platformin a non-limited operation environment, and achieves a better effect in an actual application scene.

Description

technical field [0001] The invention belongs to the field of machine vision (or intelligent transportation), and in particular relates to a vehicle type recognition algorithm based on machine vision and deep learning. Background technique [0002] At present, machine vision and deep learning technology are widely used in intelligent transportation systems, such as license plate recognition, traffic flow detection, vehicle violation detection, road vehicle type recognition and other fields. [0003] Among them, vehicle recognition refers to the application of machine vision technology to use the digital image or video collected by the camera as image input, and use the target detection framework in deep learning to identify the type of vehicle in the image, and use it as one of the basis for judging vehicle violations. [0004] However, in the field of intelligent transportation, because some images are collected through the use of vehicle-mounted mobile platforms, the overla...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06V20/54G06V2201/08G06N3/045G06F18/241
Inventor 高明煜罗强董哲康何志伟杨宇翔
Owner HANGZHOU DIANZI UNIV
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