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A Naive Bayesian Approach for Color Recognition of License Plates

机译:一种朴素的贝叶斯探索牌照牌照的方法

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Color recognition of license plates is an important step to License Plate Recognition (LPR) system. In order to perform color recognition more effectively, an algorithm based on Naive Bayesian approach is proposed in this paper. To improve the efficiency of color recognition, the multiclass problem is converted into two binary problems based on the reverse color information of plate images. Color features of license plates are extracted in the HSV (hue-saturation-value) color space. Statistical information about color features for each type of license plates are obtained from training samples. And color classifier is built according to the Naive Bayesian rule. Comparison experiments were conducted on three different test sets. And the experimental results show that the proposed algorithm achieves good recognition performances.
机译:牌照的颜色识别是牌照牌照(LPR)系统的重要步骤。为了更有效地执行颜色识别,本文提出了一种基于朴素贝叶斯方法的算法。为了提高颜色识别的效率,基于板图像的反向颜色信息,将多种子序问题转换为两个二元问题。在HSV(色调饱和值)颜色空间中提取牌照的颜色特征。有关每种类型牌照颜色特征的统计信息从训练样本获得。和彩色分类器是根据朴素贝叶斯规则建造的。对比较实验在三种不同的测试组上进行。实验结果表明,该算法达到了良好的识别性能。

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