车辆外观特征识别:车辆型号、颜色和车牌分类的计算机视觉方法

Aayush Agarwal, Sandeep Shinde, Sagar Mohite, Swati Jadhav
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引用次数: 1

摘要

本文拟从外观上分析车辆特征的识别。与人脸识别等其他用例相比,基于图像的目标识别已经得到了深入的研究,而车辆特征识别领域却没有得到足够的重视。我们使用目标识别算法和图像分类方法来确定汽车的品牌(制造商)、颜色和车牌信息。我们使用车辆徽标作为标准之一,这样我们就可以区分来自不同制造商的形状相似的汽车。此外,我们还创建了一个场景,用于在现实世界中识别汽车属性。本文提出了一种基于交通摄像机图像的车辆分类和车辆检测的智能方法。我们已经证明,汽车的一些元素,比如制造商和牌照,是能够被精确检测到的。所提出的方法可以改善当前交通摄像系统的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Vehicle Characteristic Recognition by Appearance: Computer Vision Methods for Vehicle Make, Color, and License Plate Classification
This paper intends to analyze the recognition of vehicle characteristics from appearance. In comparison to other use cases, like facial recognition, where image-based target recognition has been thoroughly researched, the field of vehicle characteristic recognition has not gotten as much attention in the literature. We use object identification algorithms and image classification methods to determine the make (manufacturer), color, and license plate information of the car. We use vehicle logos as one of the criteria so that we can distinguish between cars with similar forms from different manufacturers. Additionally, we created a scenario for recognizing car attributes in the actual world. An intelligent method for classifying various car types and detecting vehicles from traffic camera images was suggested in this study. We have shown that elements of a car, such as manufacturer and license plates, are capable of being precisely detected. The performance of the current traffic camera systems might be improved by the suggested approach.
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