复杂道路环境下的车辆牌照检测与识别

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中图分类号：TP391.4;U491.116 文献标志码：B

Vehicle license plate detection and recognition in complex road environments

WAN Yuhao

（Schools of Information and Communication Engineering，Shanghai University，Shanghai 2OO444，China）

Abstract： A gray binarization image preprocessing method based on a global threshold is proposed to aim at the issues of poor positioning detection eect and low recognition accuracy caused by tilt，blurring and occlusion of license plates in complex road.YoloV5l algorithm is adopted to conduct positioning detection and evaluate detection results on data sets in the post-processng stage.R-CNN model is used to recognize the license plate image characters after location detection. The results show that when the training process continues to 10O rounds，compared with the Faster R-CNN algorithm， the mean average precision （mAP）of the model detection is improved by 9.2% ，and the recognition accuracy is improved by 17.33% ，which verifies the effectiveness and superiority of this method in detecting and recognizing license plates.

Key words： gray binarization； image denoising；deep learning； YoloV5l； license plate location；R-CNN ；character recognition；object detection

0引言

目前，车辆牌照识别（vehiclelicenseplaterecognition，VLPR）技术被广泛应用于无人值守停车区域、道路安全管理等智能交通监管系统。（剩余11132字）