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Heuristics for license plate localization and hardware implementation of Automatic License Plate Recognition (ALPR) system

机译:车牌定位和自动车牌识别(ALPR)系统的硬件实现的启发式

摘要

The project “Heuristics for license plate localization and hardware implementation of Automatic License Plate Recognition (ALPR) system” deals with detection and recognition of license plate from a captured front view of any car. The work follows all the steps in an ALPR system like preprocessing, segmentation, and license plate identification, extraction of individual characters and finally recognition of each character to form a string to match with the registered License plate numbers. The main contribution in the work is to expedite the number plate isolation from a set of segmented candidates. It utilizes a set of heuristics typically transition from object to background and vice-versa, aspect ratio of the bounding boxes. This narrow down the number of candidates for further processing and further, we suggest a rank based identification of each character in the number plate. The process scheme along with the existing methodologies is integrated to develop the overall ALPR system. A set of standard images collected from internet as well as self-collected car images of staff vehicles are used for simulation. The experiments are conducted using OpenCV. For validation, a working ALPR hardware prototype is developed using AVR development board (ATmega32 microcontroller), GP2D120 distance measurement sensor (IR-sensor).Interfacing between PC and controller-board is done using serial port. The model works with an accuracy of 80%. The ALPR system has a further scope to improve the recognition speed using parallel processing of various sub-steps.
机译:项目“用于车牌定位和自动车牌识别(ALPR)系统的硬件实现的启发式”的项目涉及从捕获的任何汽车的正视图中检测和识别车牌。这项工作遵循ALPR系统中的所有步骤,例如预处理,分段和车牌识别,提取单个字符并最终识别每个字符以形成与注册车牌号匹配的字符串。这项工作的主要贡献是加快了车牌与一组细分候选者之间的隔离。它利用一组启发式方法,通常从对象到背景转换,反之亦然,即边界框的宽高比。这样可以缩小候选字符的数量,以便进行进一步处理,此外,我们建议对车牌中的每个字符进行基于等级的识别。流程方案与现有方法集成在一起,以开发整个ALPR系统。从互联网收集的一组标准图像以及工作人员车辆的自收集汽车图像用于仿真。实验是使用OpenCV进行的。为了进行验证,使用AVR开发板(ATmega32微控制器),GP2D120距离测量传感器(IR传感器)开发了有效的ALPR硬件原型,并使用串行端口完成了PC与控制器板之间的接口。该模型的准确度为80%。 ALPR系统具有进一步的范围,可以通过并行处理各个子步骤来提高识别速度。

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    Chhabada Sandeep Singh;

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  • 年度 2012
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