Webcam-Based Finger Detection Using Mediapipe - Rudi, Fachri Yanuar; Syahputra, Guntur; Erdiansyah, Umri; Safar, Ilham (Politeknik Negeri Lhokseumawe, 2025)
The development of multimedia-based learning tools continues to advance alongside technological innovations, particularly in recognizing parts of the human body such as fingers. This study aims to develop an interactive learning application for identifying the names of fingers using motion capture technology through Mediapipe and the Python programming language. The application utilizes a webcam as the input device to detect hand positions and movements in real-time. The system is designed to recognize individual fingers by comparing the length of finger segments and the width of the palm, based on hand landmark data provided by the Mediapipe Hands module. Testing results show that the application achieved a 90% success rate across 50 trials. These results indicate that Mediapipe technology holds significant potential for use in the development of interactive and educational learning media.