基于移动摄像头的移动车辆车牌识别

Chao-Ho Chen, Tsong-Yi Chen, Min-Tsung Wu, T. Tang, Wu-Chih Hu
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引用次数: 15

摘要

本文研究了一种基于车载摄像机的移动车辆车牌识别系统。本文提出的LPR方法主要包括预处理、车牌定位和字符分割与识别。首先,利用所提出的边缘检测方法和基于梯度的二值化方法,从采集的车牌图像中增强车牌可能存在的区域;然后,通过分析水平投影和角点分布,选择正确的板区;首先对分割后的车牌区域进行垂直索贝尔处理,然后利用所提出的加权二值化方法对车牌的每个字符进行分割,然后进行偏态校正。最后,应用概率神经网络(PNN)技术对每个被分割的字符进行识别。实验结果表明,车牌定位和车牌识别的准确率分别可达到91.7%和88.5%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
License Plate Recognition for Moving Vehicles Using a Moving Camera
This paper is dedicated to a license plate recognition (LPR) system for moving vehicles by using car video camera. The proposed LPR method mainly consists of preprocessing, plate location, and character segmentation & recognition. At irst, the possible regions of license plate are enhanced from the captured images through the proposed edge detection method and gradient-based binarization. Then, the correct plate regions are selected by analyzing the horizontal projection and the corner distribution. A vertical Sobel processing is performed on the segmented license-plate region and then the proposed weighted-binarization method is employed to segment each character of the license, followed by the skew correction. Finally, a probabilistic neural network (PNN) technique is applied to recognize each segmented character. Experimental results show that the accuracy rates of license-plate location and license-plate recognition can achieve 91.7% and 88.5%, respectively.
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