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Thermal-image processing and statistical analysis for vehicle category in nighttime traffic

机译:夜间交通中车辆类别的热图像处理和统计分析

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The automatic tollgate at highway entrance and exit needs to categorize vehicle in order to collect highway passing fee especially at night time. This paper proposes a method of vehicle categorization in nighttime traffic using thermal-image processing and statistical analysis. To recognize the vehicular types, statistical relation between thermal features of engine heat, windscreen and others are utilized in this method. Firstly, appropriate threshold values for classifying the thermal features are automatically determined, entire area of the thermal image is then divided into blocks, and thermal features classified in all blocks by the threshold values are finally integrated for vehicle type categorization. To evaluate the performance of proposed method, experiments with 2937 samples of cars, vans and trucks are categorized, and the results approximately reveal 95.51% accuracy. (C) 2017 Elsevier Inc. All rights reserved.
机译:高速公路出入口处的自动收费站需要对车辆进行分类,以收取高速公路通行费,尤其是在夜间。提出了一种利用热图像处理和统计分析的夜间交通车辆分类方法。为了识别车辆类型,在该方法中利用了发动机热量,挡风玻璃等的热特征之间的统计关系。首先,自动确定用于对热特征进行分类的适当阈值,然后将热图像的整个区域划分为多个块,并且最终将通过阈值在所有块中分类的热特征进行积分以用于车辆类型分类。为了评估所提出方法的性能,对2937个汽车,厢式货车和卡车样品进行了分类,结果大约表明95.51%的准确性。 (C)2017 Elsevier Inc.保留所有权利。

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