Abstract
The goal of the proposed work is to execute the accessible method to identify the stop board and red movement motion for a self-governing auto that makes a move as indicated by activity motion with the assistance of raspberry pi3 board. The framework likewise utilizes ultrasonic sensor for separation estimation with the end goal of speed control of vehicle to maintain a strategic distance from impact with ahead of vehicle. Rpi camera module is used for billboard recognition, and ultrasonic sensors are utilized to get the separation data from the genuine world. The proposed framework will get the picture of this present reality from the camera and after that covering and shape strategies are utilized to recognize the red signs of the activity and to decide the movement board signs like stop board framework will utilize haar course method to decide the stop words. So auto will have the capacity to make a move and diminishes the odds of human blunders like driver oversights that outcomes street mischances. The coding for this entire framework is in Python, and for picture handling, opencv is utilized that is much effective as contrast with the MATLAB. Ultrasonic sensor is utilized for the deterrent location set-up of camera since separation finding from the camera is more unpredictable and computational as contrast with the ultrasonic sensor. Ultrasonic sensor specifically gives the snag separate in front of it without more mind-boggling calculations.
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Tiwari, R., Singh, D.K. (2018). Vehicle Control Using Raspberry pi and Image Processing. In: Singh, R., Choudhury, S., Gehlot, A. (eds) Intelligent Communication, Control and Devices. Advances in Intelligent Systems and Computing, vol 624. Springer, Singapore. https://doi.org/10.1007/978-981-10-5903-2_24
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DOI: https://doi.org/10.1007/978-981-10-5903-2_24
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