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Vehicle Identification Based on the Model

机译:基于模型的车辆识别

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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.
机译:现在,一天的车辆识别已成为广阔的研究领域。车辆识别有几种应用,如在自动停车,收费栅极管理等中,由于许多应用,计算机视觉中的车辆识别已成为智能运输系统的研究区域(其)。来自不同制造商的许多不同的车辆日益增加。分析这些车辆的属性并识别不同车辆是一个复杂的任务。该项目的主要目标是车辆识别。通过对其标志性牌照的识别进行识别,可以识别车辆,但是在操纵牌照,丢失或覆盖时,车牌识别系统不起作用。车辆的另一个重要属性是其标识,其中包含有关汽车的重要信息,因为它不能轻易更改。徽标在识别车辆中起着重要作用。这里的车辆识别基于徽标集中集中,以便为制造商名称或品牌提供。通过使用ROI选择提取徽标来执行车辆识别。然后通过使用灰度级共发生矩阵特征提取方法,提取特征,并基于概率神经网络执行分类。

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