Low-Resolution Chinese Character Recognition of Vehicle License Plate Based on ALBP and Gabor Filters

Ye Wang, Honggang Zhang, Xu Fang, Jun Guo
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引用次数: 20

Abstract

Low-resolution Chinese character recognition of vehicle license plate is always a difficult problem. On the basic of existing Local Binary Patterns(LBP) operator, we propose a powerful and low-computation advanced LBP(ALBP)operator as feature extraction, and apply into Chinese character recognition for the first time. As local feature extraction operater, it produces a feature excursion for characters of barycenter departure. Therefore we use the advantage of global analysis of Gabor filters, construct Gabor filters to recognize characters of barycenter departure. The experimental results show the method is robust against low quality Chinese characters and more adaptive than conventional approach both on preciseness and recognition speed.
基于ALBP和Gabor滤波器的车牌低分辨率汉字识别
车牌的低分辨率汉字识别一直是一个难题。在现有局部二值模式(LBP)算子的基础上,提出了一种功能强大、计算量低的高级LBP算子作为特征提取,并首次应用于汉字识别。作为局部特征提取算子,对质心偏离的特征进行特征偏移。因此,我们利用Gabor滤波器的全局分析优势,构造Gabor滤波器来识别重心偏离的特征。实验结果表明,该方法对低质量汉字具有较强的鲁棒性,在正确率和识别速度上都比传统方法具有更强的适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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