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首页> 外文期刊>Procedia Computer Science >Automated Vehicle Classification with Image Processing and Computational Intelligence
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Automated Vehicle Classification with Image Processing and Computational Intelligence

机译：具有图像处理和计算智能的自动车辆分类

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摘要

Classification of vehicles is an important part of an Intelligent Transportation System. In this study, image processing and machine learning techniques are used to classify vehicles in dedicated lanes. Images containing side view profile of vehicles are constructed using a commercially available light curtain. This capability makes the results robust to the variations in operational and environmental conditions. Time warping is applied to compensate for speed variations in traffic. Features such as windows and hollow areas are extracted to discriminate motorcycles against automobiles. The circularity and skeleton complexity values are used as features for the classifier. K-nearest neighbor and decision tree are chosen as the classifier models. The proposed method is evaluated on a public highway and promising classification results are achieved.
机译：车辆分类是智能交通系统的重要组成部分。在这项研究中，图像处理和机器学习技术用于对专用车道上的车辆进行分类。使用市售的光幕来构造包含车辆的侧面轮廓的图像。这种功能使结果对于操作和环境条件的变化具有鲁棒性。应用时间扭曲来补偿流量的速度变化。提取诸如窗户和空心区域之类的特征以区分摩托车与汽车。圆度和骨架复杂度值用作分类器的特征。选择K最近邻和决策树作为分类器模型。该方法在公路上进行了评估，并取得了可喜的分类结果。

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