Fuzzy logic based on image processing to control a dc motor

Abstract

Abstract Image Processing was a form of processing of input data signals in the form of images. This input image was transformed into another image with certain techniques. The techniques used in image processing were intensity adjustment, histogram equalization, thresholding, motion blur, canny and median filtering. Image processing could be used to do tracking. This tracking was a job to follow the movement of the object caught on the camera. Tracking using image processing could be utilized in various fields. In this study, the DC motor control system was discussed by utilizing image processing to detect hexagon shaped objects. In addition to detecting the shape that was detected, this image processing was also to detect color. The color of the detected object was orange. This motor speed followed the object’s motion horizontally. So, if the object was shifted to the right, the system will rotate slowly, whereas if it was moved to the left, the system will rotate quickly. This motor control used a PG45 motor, webcam, and personal computer. The success of reading the location of the area and providing PWM output on the motor achieved almost match between simulation and experiment.