Fingerprints are used in many fields as important biological data of people. As one of people's important personal privacy, fingerprints are also prone to leakage. Images and videos posted on social media are invitations to this problem. Research in the direction of protection of fingerprint privacy is nearly vacant. Therefore, this paper presents a technical implementation for locating and erasure human fingerprints for videos. This implementation adopted Google's open-source MediaPipe machine learning framework to identify the hand in the frame and obtain crucial landmark information. The fingerprint core range and finger state are deduced from landmark points' positional relationship and distance. This method can efficiently erase as many as 88% of frames with one hand presenting.
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