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Vehicle Control Using Raspberrypi and Image Processing

机译:使用Raspberrypi和图像处理进行车辆控制

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The objective of the proposed work is to implement the available technique to detect the stop board and red traffic signal for an autonomous car that takes action according to traffic signal with the help of raspberry pi3 board. The system also uses ultrasonic sensor for distance measurement for the purpose of speed control of vehicle to avoid collision with ahead vehicle. Rpi camera module is ued for signboard detection and ultrasonic sensors are used to get the distance information from the real world.The proposed system will get the image of the real world from the camera and then masking and contour techniques are used to detect the red signals of the traffic and To determine the traffic board signs like stop board system will use haar cascade technique to determine the stop words.So car will be able to take action and reduces the chances of human errors like driver mistakes that results road accidents .The coding for this whole system is in python and for image processing opencv is used that is much efficient as compare to the matlab .Ultrasonic sensor is used for the obstacle detection in place of camera because distance finding from the camera is more complex and computational as compare to the ultrasonic sensor. Ultrasonic sensor directly gives the obstacle distance infront of it without more complex computations.
机译:拟议工作的目的是实施一种可用技术来检测自动驾驶汽车的停车板和红色交通信号,该自动驾驶汽车借助树莓派pi3板根据交通信号采取行动。该系统还使用超声波传感器进行距离测量,以控制车辆的速度,避免与前方车辆发生碰撞。 Rpi摄像头模块用于招牌检测,超声波传感器用于获取真实世界的距离信息,所提出的系统将从摄像头获取真实世界的图像,然后使用遮罩和轮廓技术检测红色信号要确定交通板的标志,例如停车板系统,将使用haar级联技术来确定停车词。因此,汽车将能够采取行动,并减少人为错误的可能性,例如导致道路交通事故的驾驶员失误。整个系统使用python进行图像处理,与matlab相比,opencv效率更高。超声波传感器用于代替摄像头进行障碍物检测,因为与摄像头的距离查找比之与之相比更加复杂且计算量大超声波传感器。超声波传感器可直接在其前方提供障碍物距离,而无需进行更复杂的计算。

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