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Vehicle Detection and Classification using Image processing

机译:使用图像处理的车辆检测和分类

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The number of vehicles has increased tremendously over the past decade. There are over 1 billion active vehicles all over the world and 60 to 70 million vehicles in India. Managing such traffic moments, providing sufficient parking lots is not an easy task. Vehicle counting and classification on busy streets will help the authorities to obtain traffic flow statistics and help them to understand and study the traffic patterns so that the can manage traffic in the most efficient way. The paper presents a way to detect, count and classify vehicles using image processing techniques. Although there has been a significant amount of research related to this, there is always a scope of improvement. The task of vehicle detection and counting is broken down into six steps: 1) Image Acquisition, 2) Image Analysis, 3) Object detection, 4) Counting, 5) Classification, 6) Display result. The algorithms which will be used to perform these tasks will includes vehicle detection and counting algorithm and road marking detection algorithm. This can also be used to monitor high ways, detect accidents, unrighteous stoppage of vehicles on roads, the traffic rules violators. Classification of vehicles will be done in one of the following categories: a) Bicycles and motorcycles, b) motor cars, c) minibus and pickup vans, d) buses trailers, trucks. This data will help to figure out the priority and maximum users of a road and design traffic patterns that will be beneficial to maximum.
机译:在过去的十年中,车辆的数量已大大增加。全世界有超过10亿辆在用车,印度有6000到7000万辆在用车。管理这样的交通时刻,提供足够的停车位并不是一件容易的事。繁忙街道上的车辆计数和分类将有助于当局获得交通流量统计信息,并帮助他们了解和研究交通模式,从而可以最有效地管理交通。本文提出了一种使用图像处理技术对车辆进行检测,计数和分类的方法。尽管对此进行了大量研究,但总有改进的余地。车辆检测和计数的任务分为六个步骤:1)图像采集,2)图像分析,3)对象检测,4)计数,5)分类,6)显示结果。将用于执行这些任务的算法将包括车辆检测和计数算法以及道路标记检测算法。这也可以用于监控高速公路,检测事故,道路上车辆的不当停车,违反交通规则的人。车辆的分类将在以下类别之一中进行:a)自行车和摩托车,b)机动车,c)小巴和轻型货车,d)公共汽车的拖车,卡车。这些数据将有助于弄清道路的优先级和最大用户,并设计出有利于最大化的交通模式。

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