Street Mark Detection Using Raspberry PI for
Self-driving System
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Abstract
Self driving is an autonomous vehicle that can follow the road with less human intervention. The
development of self driving utilizes various methods such as radar, lidar, GPS, camera, or combination of
them. In this research, street mark detection system was designed using webcam and raspberry-pi mini
computer for processing the image. The image was processed by HSV color filtering method. The
processing rate of this algorithm was 137.98 ms correspondinig to 7.2 FPS. The self-driving prototype was
found to be working optimally for “hue” threshold of 0-179, “saturation” threshold of 0-30, and “value”
threshold of 200-255. Street mark detection has been obtained from the coordinates of street mark object
which had range 4-167 on x axis and 4-139 on y axis. As a result, we have successfully built the street
mark detection by COG method more effectively and smoothly in detection in comparison with Hough
transform method