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License Plate Detection Based on Rectangular Features and Multilevel Thresholding

机译:基于矩形特征和多级阈值的车牌检测

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Rapid advancement of technology in artificial intelligence and computer science knowledge and then feel the need to search and secure automated systems are because of the appearance of intelligent systems based on image processing and spread this knowledge. One of these intelligent systems is license plate recognition (LPR) system. LPR plays an important role in intelligent transportation system; however, plate region extraction is the key step before the final recognition. In this paper, an effective license plate extraction algorithm is proposed based on geometrical features and multilevel thresholding to identify and segment the license plate from the image. Experimental results show that the technique achieved promising accuracy.
机译:人工智能和计算机科学知识的技术飞速发展,然后觉得需要搜索和保护自动化系统是因为出现了基于图像处理并传播这种知识的智能系统。这些智能系统之一是车牌识别(LPR)系统。 LPR在智能交通系统中起着重要作用。但是,提取板块区域是最终识别之前的关键步骤。本文提出了一种基于几何特征和多级阈值的有效车牌提取算法,用于从图像中识别和分割车牌。实验结果表明,该技术具有良好的准确性。

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