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Performance comparison of License Plate Recognition System using multi-features and SVM

机译:使用多功能和SVM的车牌识别系统性能比较

摘要

Feature extractor is one major factor in many image processing applications precisely in character recognition. The objective of this paper is to propose and to choose the best feature extractor for Malaysian licence plate recognition system. An enhanced Geometrical Feature Topological Analysis is proposed as a feature extractor and support vector machine is used as the classification technique. The proposed techniques and known feature extractors were used to justify its robustness for license plate recognition problem in precise. Previous research in the same domain, has applied straight pixels as the features. However, this approach is significantly acquire more time to execute the final recognition output typically in license plate recognition applications. Consequently, an alternative called the geometrical features with various combination techniques are proposed to enhance the overall performance in license plate recognition.
机译:特征提取器是精确识别字符的许多图像处理应用程序中的一个主要因素。本文的目的是为马来西亚车牌识别系统提出并选择最佳特征提取器。提出了一种增强的几何特征拓扑分析作为特征提取器,并使用支持向量机作为分类技术。提出的技术和已知的特征提取器用于精确证明其对于车牌识别问题的鲁棒性。在同一领域的先前研究已将直线像素用作特征。但是,这种方法明显需要更多的时间来执行车牌识别应用程序中的最终识别输出。因此,提出了一种具有各种组合技术的称为几何特征的替代方案,以增强车牌识别的整体性能。

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