基于局部二值模式特征的车牌定位

2019 International Conference on Recent Advances in Energy-efficient Computing and Communication (ICRAECC) Pub Date : 2019-03-01 DOI:10.1109/ICRAECC43874.2019.8994964

A. X, Adline N Titus, A. A

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引用次数: 1

摘要

由于道路上车辆的增加，智能交通系统(ITS)的重要性日益增加。车牌自动检测(ALPD)仍然是一个具有挑战性的任务，由于天气，遮挡，脏车牌(LP)和其他一些因素。本文提出了局部二值模式(LBP)特征用于LP区域的检测。使用级联Adaboost分类器对候选区域进行分类。输入图像选择不同的条件，如遮挡，低对比度，脏LP图像和光照差。该方法在600幅图像上进行了测试。该方法的检出率为96.8%。

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Vehicle License Plate Localization based on Local Binary Pattern Features

The importance of Intelligent Transportation System (ITS) is increasing because of increasing the number of vehicles on the roads. Automatic License Plate Detection (ALPD) is still a challenging task based on weather, occlusion, dirty License Plates (LP) and some other factors. In this paper Local Binary Pattern (LBP) feature is proposed for the detection of LP region. Cascaded Adaboost classifier is used for the classification of candidate region. The input images are chosen with different conditions such as occlusion, low contrast, dirty LP images and poor illumination. The proposed technique is tested on 600 images. This method achieves 96.8% detection rate.

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2019 International Conference on Recent Advances in Energy-efficient Computing and Communication (ICRAECC)

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