A Study on Contour Feature Algorithm for Vehicle Type Recognition

Weihua Wang
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引用次数: 5

Abstract

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.
车辆类型识别的轮廓特征算法研究
在智能交通系统中,车辆类型自动识别具有重要的意义。神经网络常用于车辆类型识别。然而,网络可能非常复杂,因此很难训练。为了解决这一问题,本文提出了一种新的基于轮廓特征的车辆类型识别方法。应用该方法从车辆的几何特征中获取车辆类型。这使得识别系统仅在给定的几何尺寸上实现,并简化了细化识别过程。这项工作的贡献有三个方面:首先,提出了一种新的提取车辆特征的进化方法;其次,给出了一种由四个步骤组成的车辆识别算法。最后,通过静态车辆图像和动态车辆视频对识别系统的性能进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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