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首页> 外文期刊>International Journal of Image Processing >A Novel Multiple License Plate Extraction Technique for Complex Background in Indian Traffic Conditions
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A Novel Multiple License Plate Extraction Technique for Complex Background in Indian Traffic Conditions

机译:印度交通条件下复杂背景的新型多牌照提取技术

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License plate recognition (LPR) is one of the most important applications of applying computer techniques towards intelligent transportation systems (ITS). In order to recognize a license plate efficiently, location and extraction of the license plate is the key step. Hence finding the position of a license plate in a vehicle image is considered to be the most crucial step of an LPR system, and this in turn greatly affects the recognition rate and overall speed of the whole system. This paper mainly deals with the detecting license plate location issues in Indian traffic conditions. The vehicles in India sometimes bare extra textual regions such as owner’s name, symbols, popular sayings and advertisement boards in addition to license plate. Situation insists for accurate discrimination of text class and fine aspect ratio analysis. In addition to this additional care taken up in this paper is to extract license plate of motorcycle (size of plate is small and double row plate), car (single as well as double row type), transport system such as bus, truck, (dirty plates) as well as multiple license plates present in an image frame under consideration. Disparity of aspect ratios is a typical feature of Indian traffic. Proposed method aims at identifying region of interest by performing a sequence of directional segmentation and morphological processing. Always the first step is of contrast enhancement, which is accomplished by using sigmoid function. In the subsequent steps, connected component analysis followed by different filtering techniques like aspect ratio analysis and plate compatible filter technique is used to find exact license plate. The proposed method is tested on large database consisting of 750 images taken in different conditions. The algorithm could detect the license plate in 742 images with success rate of 99.2%.
机译:车牌识别(LPR)是将计算机技术应用于智能交通系统(ITS)的最重要应用之一。为了有效地识别牌照,牌照的定位和提取是关键步骤。因此,找到车牌在车辆图像中的位置被认为是LPR系统最关键的步骤,而这反过来又极大地影响了整个系统的识别率和整体速度。本文主要讨论在印度交通状况下检测车牌位置的问题。印度的车辆有时除了车牌外还带有一些文字区域,例如车主的姓名,符号,流行语和广告板。情境要求准确区分文本类并进行精细的宽高比分析。除了本文中需要注意的其他事项外,还要提取摩托车(车牌的大小为小号和双排板),汽车(单排和双排型),运输系统(如公共汽车,卡车,正在考虑的图像帧中是否有脏板)以及多个牌照。长宽比的差异是印度流量的典型特征。所提出的方法旨在通过执行一系列方向分割和形态学处理来识别感兴趣区域。第一步始终是增强对比度,这是通过使用S型函数来完成的。在随后的步骤中,使用连接的组件分析,然后使用不同的过滤技术(例如长宽比分析和车牌兼容的过滤器技术)来查找确切的车牌。在大型数据库上测试了该方法,该数据库包含在不同条件下拍摄的750张图像。该算法可以检测742张图像中的车牌,成功率为99.2%。

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