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A Study on Contour Feature Algorithm for Vehicle Type Recognition

机译:轮廓线特征算法在车辆类型识别中的研究

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Vehicle type automatic recognition is of great important today in intelligent transportation system. And neural network is often applied to recognize the vehicle type. However, the network can be very complex and therefore difficult to be trained. In order to cope with such issues, a new developed vehicle type recognition method based on contour feature is presented in this study. It is applied to obtain the vehicle type from the geometrical feature of the vehicle. This enables the implementation of the recognition system only in given geometrical size and simplifies the thinning recognize procedure. The contribution of this work is threefold: At first, a novel evolutionary methodology for extracting vehicle feature is presented. Secondly, a vehicle recognition algorithm consisting of four steps is demonstrated. Finally, the performance of the recognition system is evaluated by not only using static vehicle image but also using dynamic vehicle video.
机译:如今,车辆类型自动识别在智能交通系统中非常重要。神经网络通常用于识别车辆类型。但是,网络可能非常复杂,因此难以训练。为了解决这些问题,本研究提出了一种新的基于轮廓特征的车辆类型识别方法。它用于从车辆的几何特征中获取车辆类型。这使得仅以给定的几何尺寸实现识别系统,并简化了稀疏识别过程。这项工作的贡献是三方面的:首先,提出了一种用于提取车辆特征的新颖的进化方法。其次,说明了由四个步骤组成的车辆识别算法。最后,不仅通过使用静态车辆图像而且通过使用动态车辆视频来评估识别系统的性能。

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