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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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.
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