Implementasi Algoritma Hough transform Pada Object Following Menggunakan Ar.Drone Quadcopter - Muhammad Tri Buwana Zulfikar Ardi; Gembong Edhi Setyawan; Fitri Utaminingrum (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2020)
Quadcopter is one type of unmanned aerial vehicle (UAV) or unmanned aircraft that has 4 rotors. At present the quadcopter control system still uses radio control. Along with the development of quadcopter technology at this time has been equipped with various features such as GPS and also a camera to take pictures or digital images from the quadcopter's point of view. Ar.Drone is an output quadcopter from the Parrot brand. Ar.Drone uses the Linux operating system so that it can be used to conduct research on quadcopter development. On the quadcopter an intelligent algorithm can be applied related to image processing so that it can be developed and one of them is object following or tracking. By using hough transform researchers are expected to be able to create an automatic navigation system for quadcopter that can be used to detect spherical objects as a basis for navigation. With the automatic navigation system can be petrified if you want to take a picture or video needed to record an object without having to do manual navigation using radio control. The navigation system automatically runs based on the position of the ball in the video streaming frame. for that frame streaming is divided into 9 frames to find out what movements the quadcopter has to do to be able to move along with the object. There are several things that must be done before the image from the front camera quadcopter can be used for the implementation of the hough transform algorithm. The process is image pre-processing, namely digital image processing including segmentation using HSV, blurring, and canny edge. In testing the position of the spherical coordinates on the frame, it can be concluded that the quadcopter can track the movement of the ball with reference to the sphere midpoint coordinate position. From the distance test, the maximum distance for detection is 4m with the percentage of successful detection of all colors at 85%.