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Tampering Detection in Oral History Video Using Watermarking

机译:使用水印的口述历史视频中的篡改检测

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The oral history videos present highly cultural and historical values. The protection of its authenticity and integrity are important. A lot of video watermarking schemes are proposed to prevent malicious attacks in recent years. An innovative algorithm is proposed in this work to resist key frames dropping and detect the subtitle tampered. Firstly, Simple Linear Iterative Clustering (SLIC) Superpixels are used to extract the natural codes of the video. Meanwhile, the targeting codes are obtained from the natural codes which are modified by the (7, 4) Hamming code error correction for identifying the watermarked frame. Secondly, the text region is located accurately by structure tensor and subtitle segmentation. Furthermore, the watermark information is composed of stroke and structural characteristic of Chinese characters. Finally, the watermark is embedded into the oral history videos based on Discrete Cosine Transform (DCT) and Singular Value Decomposition (SVD) robustly. The experimental results show the algorithm is against to several attacks including tampering texts, frames dropping and compression.
机译:口述历史视频展现了高度的文化和历史价值。保护其真实性和完整性很重要。近年来,提出了许多视频水印方案以防止恶意攻击。在这项工作中提出了一种创新的算法来抵抗关键帧丢失和检测字幕被篡改。首先,简单线性迭代聚类(SLIC)超像素用于提取视频的自然码。同时,从通过(7、4)汉明码纠错而修改的自然码中获得目标码,以识别水印帧。其次,通过结构张量和字幕分割准确地定位文本区域。此外,水印信息由笔划和汉字的结构特征组成。最后,将水印强大地嵌入到基于离散余弦变换(DCT)和奇异值分解(SVD)的口述历史视频中。实验结果表明,该算法可以抵御多种攻击,包括篡改文本,丢帧和压缩。

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