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Vehicle number plate detection and recognition using bounding box method

机译:边界框法的车牌识别与识别

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The use of vehicles in our life is increasing exponentially day by day and as increasing vehicles are violating the traffic rules, theft of vehicles, entering in restricted areas, high number of accidents lead to increase in the crime rates linearly. For any vehicle to be recognized, vehicle license plate detection will play a major significant role in this active world. For finding vehicles commonly used in field of security and safety system, LPDR plays a significant role and we need to recognize vehicles registration number at a certain distance. This paper has four major steps as follows: Preprocessing of captured image, Extracting license number plate region, Segmentation and Character Recognition of license plate. In pre-processing the desired vehicle image is taken through the digital camera, brightness of image is adjusted, noise removal using filters and image is converted to gray scale. Exactions of license plate region consist of finding the edges in the image where exact location of licenses plate is located and crop it into rectangular frame. Segmentation plays a vital role in vehicle licenses plate recognition; the legibility of character recognition completely relies on the segmentation done. The approach which we have used is simple but appropriate. First we segmented all characters in the image (LP) using Bounding box method. Finally, recognition of each character is done. The template matching method is used for recognition each character in the vehicle license plate.
机译:车辆的使用在我们的生活中呈指数级增长,并且随着越来越多的车辆违反交通规则,车辆被盗,进入禁区,大量事故导致犯罪率呈线性增长。对于要识别的任何车辆,车牌检测将在这个活跃的世界中发挥重要作用。为了找到在安保和安全系统领域中常用的车辆,LPDR发挥了重要作用,我们需要在一定距离内识别车辆的注册号。本文包括四个主要步骤:捕获图像的预处理,提取车牌区域,车牌分割和字符识别。在预处理过程中,通过数码相机拍摄所需的车辆图像,调整图像的亮度,使用滤镜去除噪声,然后将图像转换为灰度。车牌区域的精确性包括在图像中找到车牌确切位置所在的边缘,并将其裁剪为矩形框。分割在车牌识别中起着至关重要的作用。字符识别的可读性完全取决于完成的分割。我们使用的方法很简单但是很合适。首先,我们使用边界框方法对图像(LP)中的所有字符进行了分割。最后,完成每个字符的识别。模板匹配方法用于识别车牌中的每个字符。

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