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首页> 外文期刊>Intelligent Transportation Systems, IEEE Transactions on >An Iranian License Plate Recognition System Based on Color Features
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An Iranian License Plate Recognition System Based on Color Features

机译：基于颜色特征的伊朗车牌识别系统

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摘要

In this paper, an Iranian vehicle license plate recognition system based on a new localization approach, which is modified to reflect the local context, is proposed, along with a hybrid classifier that recognizes license plate characters. The method presented here is based on a modified template-matching technique by the analysis of target color pixels to detect the location of a vehicle’s license plate. A modified strip search enables localization of the standard color-geometric template utilized in Iran and several European countries. This approach uses periodic strip search to find the hue of each pixel on demand. In addition, when a group of target pixels is detected, it is analyzed to verify that its shape and aspect ratio match those of the standard license plate. In addition to being scale and rotation invariant, this method avoids time-consuming image algorithms and transformations for the whole image pixels, such as resizing and Hough, Fourier, and wavelet transforms, thereby cutting down the detection response time. License plate characters are recognized by a hybrid classifier that comprises a decision tree and a support vector machine with a homogeneous fifth-degree polynomial kernel. The performance detection rate and the overall system performance achieved are 96% and 94%, respectively.
机译：本文提出了一种基于新定位方法的伊朗车辆牌照识别系统，该系统经过修改以反映当地情况，并提出了一种可识别牌照字符的混合分类器。本文介绍的方法基于一种改进的模板匹配技术，该技术通过分析目标颜色像素以检测车辆牌照的位置。修改后的条形搜索功能可以对伊朗和几个欧洲国家/地区使用的标准颜色几何模板进行本地化。该方法使用定期条带搜索来按需查找每个像素的色相。另外，当检测到一组目标像素时，将对其进行分析以验证其形状和纵横比是否与标准车牌的形状和纵横比匹配。除了缩放和旋转不变外，该方法还避免了耗时的图像算法和整个图像像素的变换，例如调整大小和进行Hough，Fourier和小波变换，从而减少了检测响应时间。车牌字符由混合分类器识别，该混合分类器包括决策树和具有均匀五次多项式核的支持向量机。性能检测率和整体系统性能分别为96％和94％。

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