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Precise 2-step segmentation of corrupted characters in License Plate Recognition applications

机译:车牌识别应用程序中损坏字符的精确两步分割

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Image-based License Plate Recognition (LPR) algorithms are the core modules of many Intelligent Transportation Systems (ITS). Different algorithms and approaches have been proposed so far. All of these methods have the following three steps in common: License Plate Localization, Character Segmentation & Character Recognition. There are many real-world issues encountered during the design of each step, including different plate formats, time-variant illumination conditions and etc. To have a reliable operator-free system, all of these need to be overcome. One of such issues which is the main focus of this article and so far has not been addressed in any previous work is the presence of characters corrupted by misplaced rivets/screws. In this paper we present a simple, yet effective technique based on traditional pattern matching methods which when combined with modern character recognition techniques, can bring up the success rates of current systems closer to 100%.
机译:基于图像的车牌识别(LPR)算法是许多智能运输系统(ITS)的核心模块。迄今为止,已经提出了不同的算法和方法。所有这些方法共有以下三个步骤:车牌定位,字符分割和字符识别。在每个步骤的设计过程中,都会遇到许多实际问题,包括不同的印版格式,随时间变化的照明条件等。要拥有可靠的免操作员系统,必须克服所有这些问题。此类问题是本文的重点,迄今为止,在以前的任何工作中都没有解决的问题是存在由于错位的铆钉/螺钉而损坏的字符。在本文中,我们提出了一种基于传统模式匹配方法的简单而有效的技术,当与现代字符识别技术结合使用时,可以使当前系统的成功率接近100%。

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