Zero-watermarking Algorithm for Audio and Video Matching Verification

Abstract

<abstract> <p>For the needs of tamper-proof detection and copyright identification of audio and video matching, this paper proposes a zero-watermark algorithm that can be used for audio and video matching verification. The algorithm segments audio and video in smaller time units, generates a video frame feature matrix based on NSCT, DCT, and SVD, and generates a sound watermark based on methods such as DWT and K-means. The zero watermark combines video, audio and copyright information. The experimental results show that the zero watermark generated by this algorithm can not only realize highly accurate matching detection and positioning of audio and video, but also well resist common single attack and combination attacks such as noise, scaling, rotation, frame attack and format conversion, which has good robustness.</p> </abstract>

Audio and Video Matching Zero‐Watermarking Algorithm Based on NSCT

“…In this way, on the one hand, it can effectively extract the stable features of audio and video segments and quickly build an optimized zero watermark. On the other hand, it can also detect the tampering of small audio or video segments in the entire audio and video stream more accurately [22]. e following experiments use the video (including audio) in H.264 coding format, which is divided into 30 audio and video segments in the experiment.…”

“…e above audio and video crosswatermarking does not provide copyright protection for audio and video at the same time but only generates watermarks based on the whole multimedia stream, which can only judge whether the whole audio and video match and cannot locate the tampering of small segments in audio and video streams. Sun et al [22] proposed a video zerowatermarking algorithm based on NSCT, DCT, DWT, and SVD. e algorithm generates zero-watermarking frame by combining audio watermark with video frame feature matrix, which can be utilized locating the attacks for the video besides verifying its copyright [22].…”

“…Sun et al [22] proposed a video zerowatermarking algorithm based on NSCT, DCT, DWT, and SVD. e algorithm generates zero-watermarking frame by combining audio watermark with video frame feature matrix, which can be utilized locating the attacks for the video besides verifying its copyright [22].…”

Video Watermarking Algorithm Based on NSCT, Pseudo 3D-DCT and NMF

“…At present, the research of digital watermarking technology for video is mainly based on spatial domain [4][5][6], compression domain [7][8][9][10][11][12] and transform domain [13][14][15][16][17][18][19][20][21]. The principle of the video watermarking algorithm in the spatial domain is to embed watermark data on the basis of a processing pixel value of a video frame image.…”

“…This kind of algorithm is designed to embed and extract the watermark in the transform domain. DWT (Discrete Wavelet Transform) [13], DCT (Discrete Cosine Transform) [14] and SVD (Singular Value Decomposition) [15] are commonly used to transform the image into the transformation domain, which then enables us to embed the watermark in the transform domain. Combining graph-based transformation, singular value decomposition and hyperchaotic encryption, Sharma et al [16] proposed a video watermarking algorithm, which can solve the address quality loss of data well; however, the algorithm is complex, and the anti-rotation attack performance is poor.…”