A Bangladeshi License Plate Detection System Based on Extracted Color Features

Sheikh Nooruddin, Falguni Ahmed Sharna, S. M. M. Ahsan
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Abstract

As the number of motorized vehicles is increasing rapidly in Bangladesh, Automatic License Plate Detection and Recognition (ALPDR) systems have become a necessity for proper management of vehicles on roads. The first phase of an ALPDR system is the detection and localization of number plates from vehicle images. In this paper, we introduce a dataset of 630 images that were manually captured. The dataset represents various real-world scenarios. We propose the use of color histograms with MinPool and MaxPool features for license plate detection and localization. The detection system was tested in multiple color spaces to observe their effect on the detection phase. The proposed and developed system is very effective and achieved high levels of correctness in the detection phase according to different metrics.
基于提取颜色特征的孟加拉车牌检测系统
随着孟加拉国机动车数量的迅速增加,车牌自动检测和识别(ALPDR)系统已成为对道路上车辆进行适当管理的必要条件。ALPDR系统的第一阶段是从车辆图像中检测和定位车牌。在本文中,我们介绍了一个由630张手动捕获的图像组成的数据集。该数据集代表了各种现实世界的场景。我们提出使用带有MinPool和MaxPool特征的颜色直方图进行车牌检测和定位。在多个色彩空间中对检测系统进行了测试,观察其对检测相位的影响。所提出和开发的系统非常有效,并且根据不同的度量在检测阶段实现了高水平的正确性。
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