Recaptured video detection based on sensor pattern noise

Abstract

With the advances in digital camcorders, video recapturing (screen camcording), which is also called camcorder theft, is becoming a significant problem. Nevertheless, little research on recaptured video detection has been undertaken. In this paper, an automated method for the detection of recaptured videos is proposed based on the shot-based sensor pattern noise (SPN). The SPN, which is considered to be the fingerprint of digital imaging sensors, is used due to its identifiable attribute. Furthermore, the differences between the production processes of the original videos and recaptured videos are analyzed, and this results in the shot-based method being proposed. Moreover, the SPN merging and high-frequency map are derived in order to overcome the low quality of the shot-based SPN. Empirical evidence from a large database of test video, including compressed and scaled video, indicates that superior performance of the proposed method.