自动车牌识别:神经网络方法

M. Fahmy
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引用次数: 55

摘要

利用图像处理技术的自动车牌识别,为获取交通数据提供了新的途径。计算机视觉技术的进步和相关设备价格的下降鼓励了视频/闭路电视摄像机的使用,使在线或离线视觉自动识别车辆成为现实。采用自动车牌读取技术,可以实现车辆自动识别系统的高精度和低处理时间。本研究的目的是探索使用BAM神经网络进行车牌识别的潜力。使用图像处理技术提取每个包含字符的位置,并将BAM神经网络应用于字符识别过程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic number-plate recognition: neural network approach
Automated number-plate recognition, using image processing techniques, is indicating new ways of capturing traffic data. Advances in computer vision technology and the falling prices of related devices encourage the use of video/closed circuit television cameras by making it practical to automatically identify vehicles visually on-line or off-line. An automatic vehicle identification system could be achieved using automated number-plate reading with high accuracy and low processing time. The objective of this research is to explore the potential of using the BAM neural network for number-plate reading. Image processing techniques are used to extract the location of each included character, and the BAM neural network is applied to the character recognition process.<>
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