In many industries, it is crucial to have an efficient and precise way of monitoring objects or individuals. Drones can be used for this purpose, such as in agriculture, to observe crop growth and detect potential issues. This makes them a valuable tool in different fields, offering greater accuracy and faster data collection. This research uses image thresholding to implement a Tello EDU RoboMaster TT quadrotor drone tracking control system. The goal is for the drone to autonomously follow different line shapes, rounded at different angles, steadily and safely. The drone's camera captures the line's contours using open-source methods, which are processed using image thresholding and binary masking techniques. A control point is generated at the centre of the contours and compared to the centre of the image to guide the drone's movements in real time. The research has successfully enabled the drone to follow lines of various shapes. © 2023 IEEE.