该文提出一种部分基矩阵稀疏约束的非负矩阵分解(Non-negative Matrix Factorization with Sparseness Constraints on Parts of the Basis Matrix,NMFSCPBM)方法,其次将水印嵌入在NMFSCPBM分解后的基矩阵大系数中,利用NMFSCPBM提取视...该文提出一种部分基矩阵稀疏约束的非负矩阵分解(Non-negative Matrix Factorization with Sparseness Constraints on Parts of the Basis Matrix,NMFSCPBM)方法,其次将水印嵌入在NMFSCPBM分解后的基矩阵大系数中,利用NMFSCPBM提取视频运动特征自适应控制水印嵌入强度。最后,在水印检测时,只要残余视频中包含有视频最小剩余子块数,就可以恢复出完整基矩阵,进而提取出完整水印。实验表明,与同类方法相比,该方法抵抗强剪切攻击的能力获得了较大程度提升。展开更多
Firstly, the nonnegative matrix factorization with sparseness constraints on parts of the basis matrix (NMFSCPBM) method is proposed in this paper. Secondly, the encrypted watermark is embedded into the big coefficien...Firstly, the nonnegative matrix factorization with sparseness constraints on parts of the basis matrix (NMFSCPBM) method is proposed in this paper. Secondly, the encrypted watermark is embedded into the big coefficients of the basis matrix that the host video is decomposed into by NMFSCPBM. At the same time, the watermark embedding strength is adaptively adjusted by the video motion characteristic coefficients extracted by NMFSCPBM method. On watermark detection, as long as the residual video contains the numbers of the least remaining sub-blocks, the complete basis matrix can be completely recovered through the decomposition of the nonnegative matrix of the least remaining sub-blocks in residual videos by NMFSCPBM, and then the complete watermark can be extracted. The experimental results show that the average intensity resistant to the various regular cropping of this scheme is up to 95.97% and that the average intensity resistant to the various irregular cropping of this scheme is up to 95.55%. The bit correct rate (BCR) values of the extracted watermark are always 100% under all of the above situations. It is proved that the watermark extraction is not limited by the cropping position and type in this scheme. Compared with other similar methods, the performance of resisting strong cropping is improved greatly.展开更多
文摘该文提出一种部分基矩阵稀疏约束的非负矩阵分解(Non-negative Matrix Factorization with Sparseness Constraints on Parts of the Basis Matrix,NMFSCPBM)方法,其次将水印嵌入在NMFSCPBM分解后的基矩阵大系数中,利用NMFSCPBM提取视频运动特征自适应控制水印嵌入强度。最后,在水印检测时,只要残余视频中包含有视频最小剩余子块数,就可以恢复出完整基矩阵,进而提取出完整水印。实验表明,与同类方法相比,该方法抵抗强剪切攻击的能力获得了较大程度提升。
文摘Firstly, the nonnegative matrix factorization with sparseness constraints on parts of the basis matrix (NMFSCPBM) method is proposed in this paper. Secondly, the encrypted watermark is embedded into the big coefficients of the basis matrix that the host video is decomposed into by NMFSCPBM. At the same time, the watermark embedding strength is adaptively adjusted by the video motion characteristic coefficients extracted by NMFSCPBM method. On watermark detection, as long as the residual video contains the numbers of the least remaining sub-blocks, the complete basis matrix can be completely recovered through the decomposition of the nonnegative matrix of the least remaining sub-blocks in residual videos by NMFSCPBM, and then the complete watermark can be extracted. The experimental results show that the average intensity resistant to the various regular cropping of this scheme is up to 95.97% and that the average intensity resistant to the various irregular cropping of this scheme is up to 95.55%. The bit correct rate (BCR) values of the extracted watermark are always 100% under all of the above situations. It is proved that the watermark extraction is not limited by the cropping position and type in this scheme. Compared with other similar methods, the performance of resisting strong cropping is improved greatly.
