基于模型的车辆识别

T. Sridevi, P. Swapna, K. Harinath
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引用次数: 10

摘要

如今,车辆识别已成为一个广泛的研究领域。车辆识别在自动泊车、收费站管理等方面有着广泛的应用,计算机视觉中的车辆识别已成为智能交通系统(ITS)的一个研究领域。有许多不同的车辆来自不同的制造商,日益增加。分析这些车辆的属性并识别不同的车辆是一项复杂的任务。这个项目的主要目标是车辆识别。车辆可以通过识别其标志性车牌来识别,但车牌识别系统在车牌被操纵、丢失或覆盖时不起作用。汽车的另一个重要属性是它的标志,它包含了关于汽车的重要信息,因为它不能轻易改变。标志在车辆识别中起着重要的作用。在这里,车辆识别主要基于徽标,以便给出制造商的名称或品牌。利用ROI选择提取徽标,实现车辆识别。然后采用灰度共现矩阵特征提取方法提取特征并基于概率神经网络进行分类。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vehicle Identification Based on the Model
Now a day's vehicle recognition has become a wide area of research. Vehicle recognition has several applications such as in automatic parking, toll gate management etc., Because of numerous applications, vehicle recognition in computer vision has become a research area in Intelligent Transport System (ITS). There are many different vehicles from different manufacturers which are increasing day by day. Analyzing the attributes of these vehicles and recognizing different vehicles is a complex task. The main objective of this project is vehicle identification. Vehicles can be identified by performing recognition of its iconic license plate but the License Plate Recognition System does not work when license plate is manipulated, missing or covered. Another important attribute of a vehicle is its logo which contains important information about the car and as it cannot be changed easily. Logo plays an important role in recognition of vehicles. Here vehicle recognition is concentrated based on logos in order to give the manufacturers name or brand. Vehicle recognition is performed by extracting logo using ROI selection. Then by using gray level co-occurrence matrix feature extraction method features are extracted and classification is performed based on probabilistic neural network.
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