基于高斯-埃尔米特矩的车牌字符识别

2010 Second International Workshop on Education Technology and Computer Science Pub Date : 2010-03-06 DOI:10.1109/ETCS.2010.591

Xiaojuan Ma, Renlong Pan, Lin Wang

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引用次数: 13

摘要

字符识别在车牌自动识别系统中起着重要的作用。本文提出了一种新的车牌字符识别方法，该方法采用二维不同阶数的高斯-埃尔米矩(ghm)作为BP神经网络的输入向量，以231个高斯-埃尔米矩为特征。该系统可在可变光照、可变板尺寸和动态背景下工作。实验结果证明了该方法的鲁棒性和有效性。

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License Plate Character Recognition Based on Gaussian-Hermite Moments

Character recognition plays an important role in the automatic license plate recognition (ALPR) system. In this paper, we propose a new method to recognize the license plates characters by using 2D Gaussian-Hermite moments (GHMs) of different orders with 231 GHMs features as the input vector of BP neural network. The system worked under variable illumination, variable size of plate and dynamic backgrounds. The experimental results demonstrate robust and efficient of our method.

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来源期刊

2010 Second International Workshop on Education Technology and Computer Science

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