Research on License Plate Recognition Based on Deep Learning in Complex Scenarios

Yinqing Tang, Benguo Yu, Fengning Liu, Anran Wang
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Abstract

The license plate angle is unfixed, the vehicle position is ununiform, and the picture is not sufficiently illuminated which leads to the decrease of license plate recognition accuracy. In order to improve the accuracy of license plate recognition, a deep learning-based license plate recognition method is proposed. For license plate location problem, YOLOv3 algorithm is used. The algorithm is more capable of recognizing small targets and is suitable for license plate location recognition that requires precise positioning. For the problem of license plate character recognition, the CNN plus multitask recognition method is proposed for recognition. The experimental results show that the accuracy of the license plate recognition method proposed in this paper reaches 96%, and the intelligent license plate recognition is realized.
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复杂场景下基于深度学习的车牌识别研究
车牌角度不固定,车辆位置不均匀,图像光照不足,导致车牌识别精度下降。为了提高车牌识别的准确率,提出了一种基于深度学习的车牌识别方法。车牌定位问题采用YOLOv3算法。该算法具有较强的小目标识别能力,适用于需要精确定位的车牌定位识别。针对车牌字符识别问题,提出了CNN +多任务识别方法进行识别。实验结果表明,本文提出的车牌识别方法准确率达到96%,实现了智能车牌识别。
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