The Intelligent Transportation Systems (ITS) are the subject of a world economic competition. They are the application of new information and communication technologies in the transport sector, to make the infrastructures more efficient, more reliable and more ecological. License Plates Recognition (LPR) is the key module of these systems, in which the License Plate Localization (LPL) is the most important stage, because it determines the speed and robustness of this module. Thus, during this step the algorithm must process the image and overcome several constraints as climatic and lighting conditions, sensors and angles variety, LPs no-standardization, and the real time processing. This paper presents a classification and comparison of License Plates Localization (LPL) algorithms and describes the advantages, disadvantages and improvements made by each of them
翻译:智能运输系统(智能运输系统)是世界经济竞争的主题,是在运输部门应用新的信息和通信技术,使基础设施更有效率、更可靠和更生态。许可证板识别(LPR)是这些系统的关键模块,许可证板识别(LPR)是其中最重要的阶段,因为它决定了该模块的速度和稳健性。因此,在这一步骤中,算法必须处理图像,克服气候和照明条件、传感器和角度种类、LP标准化和实时处理等若干制约因素。本文对许可证板本地化(LPL)算法进行了分类和比较,并描述了其中每一种方法的优点、缺点和改进。