This research focuses on object detection through color matching, enabling machines to detect objects based on specific colors using OpenCV, a Python library widely used in computer vision projects. As a form of Machine Learning and Artificial Intelligence, this method allows machines to automatically learn and classify objects by simulating the human visual system. The study aims to enable a machine to detect and locate a ball through digital image processing using a webcam. The research method includes digital image processing, implementation on a Raspberry Pi, and testing on a robot, where logic is applied to guide the robot toward the ball by detecting its color. The outcome is an object detection system that identifies the ball’s position in two dimensions based on its specific color. In this case, the RGB code (164, 122, 0) and a minimum ball size of 10 radians were successfully implemented on the robot. However, the system has limitations under certain conditions. Future improvements will involve integrating TensorFlow for dataset processing and OpenCV for real-time object detection to achieve more accurate results.