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《信息技术》2017,(10)
随着视频编辑软件的日益强大,视频内容篡改问题时常发生,对视频数据的破坏(包括帧删除,剪切,编辑)造成了视频无法提供真实可靠的参考信息。课题针对视频内容完整性问题进行方案研究,利用视频邻近像素的时空相关特性,采用合适的嵌入算法,将视频相关信息(包含用户名,视频设备编号,时间戳,帧序列号,哈希值)隐藏在视频编码压缩域中。在视频解码阶段,按照嵌入方案对应的映射规则将隐藏信息提取出来,重新计算提取信息的哈希值,并与原始的哈希值比对,根据比对结果判断视频信息完整性是否遭到破坏。实验结果表明该方案不仅对视频质量没有观感上的影响,同时能够有效地检测帧编辑、删除、替换等视频完整性威胁,实现了高清视频内容完整性检测,具有良好的应用意义。 相似文献
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感知哈希(Perceptual Hashing)是多媒体数据集到摘要集的单向映射,为多媒体数字内容的标识、检索、认证等应用提供了安全可靠的技术支撑.本文提出一种融合视觉感知及时空域特征的视频感知哈希算法.算法首先对视频序列每一帧进行随机可重叠分块,并计算每个分块以像素为单位的亮度均值,在某一步长下,以同一帧的分块亮度差作为视频帧空域特征,以不同视频帧相同位置的分块亮度差作为时域特征,通过哈希量化得到时空域感知哈希,通过时空域感知哈希融合,最后得到简洁的视频唯一标识——摘要哈希.实验结果表明,该算法表现出较好的鲁棒性与区分性,通过相似度拟合图算法分析,可以实现视频篡改的准确检测及定位. 相似文献
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针对视频完整性和版权保护的安全需求,为了保障视频的真实性和合法性,提出了一种基于空时特征的指纹算法。算法借鉴了视觉哈希的思想,利用视频内运动和变化的信息来生成内容特征,并通过MD5哈希算法将特征和用户私钥生成指纹信息。算法利用改进的H.264扩频水印方案,将指纹信息嵌入视频帧中,实现了H.264视频内容完整性的认证,并能在存在篡改的情况下有效识别视频中被篡改帧在序列中的位置。 相似文献
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为了提高高维空间近邻搜索算法的查询性能,本文结合DSH算法和迭代PCA方法的优点提出迭代PCA哈希算法.该算法查询效果良好,充分利用数据集的分布信息、有严格的理论保证.该算法在达到相同精度的条件下较LSH算法和DSH算法查询花费时间少.该算法提供了一种解决近邻搜索问题有效方法. 相似文献
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希望设计一套自动化,智能化,高效率的视频版权认证系统,系统总体采用了五层结构,设计了帧内数据的采样方法和由帧内采样数据构成的采样值数组,对该采样值数组进行哈希变换,求得了基本特征值,将得到的值组织成了四树权帧顺序寻址多层哈希树,将该哈希树与其他数据一起组织成了数据区块,本区块包含着前一数据区块的加密哈希值和当前时间戳,计算本数据区块的哈希值,将其加密存储在本区块的最后的数据位置,形成了数据区块链,对封面、封底区块进行加密,对整个数据打包,形成视频节目自动版权证书,论述了容错机制. 相似文献
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局部线性嵌入(LLE)和邻域保留嵌入(NPE)等流形学习方法可以提取高光谱数据的主要结构特征,有助于对数据的理解和进一步处理。但是,这些方法忽视了高光谱图像中相邻像素之间的相关性。针对这个问题,提出一种基于空间一致性思想的邻域保留嵌入(SC-NPE)特征提取算法,通过一个优化的局部线性嵌入,并考虑相邻像素的相关特性,在高维空间建立数据的局部邻域结构。然后寻找一个优化的变换矩阵,将局部邻域结构投影到低维空间,实现数据的特征提取。与LLE和NPE算法相比,SC-NPE既考虑高光谱数据的流形结构,又考虑了其图像域空间信息,可以更好地应用在高光谱数据的特征提取过程中。实验结果表明,SC-NPE特征提取算法在高光谱图像分类方面的性能明显优于其他同类算法。 相似文献
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基于外存的位置敏感搜索方法 总被引:1,自引:0,他引:1
位置敏感哈希在信息检索、目标识别和视频语义搜索等领域得到了广泛应用,与基于树的方法相比,它们虽然初步解决了高维检索问题,但这些基于主存的方法在实际应用中仍有较大的局限性。为解决大数据集快速检索问题,在E2LSH基础上提出了基于外存的位置敏感搜索方法,将数据集各点通过位置敏感哈希函数族进行映射并在外存建立索引文件,实验证明该方法在检索准确率几乎相当的情况下检索时间大大缩短。 相似文献
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Video hashing is a useful technique of many multimedia systems, such as video copy detection, video authentication, tampering localization, video retrieval, and anti-privacy search. In this paper, we propose a novel video hashing with secondary frames and invariant moments. An important contribution is the secondary frame construction with 3D discrete wavelet transform, which can reach initial data compression and robustness against noise and compression. In addition, since invariant moments are robust and discriminative features, hash generation based on invariant moments extracted from secondary frames can ensure good classification of the proposed video hashing. Extensive experiments on 8300 videos are conducted to validate efficiency of the proposed video hashing. The results show that the proposed video hashing can resist many digital operations and has good discrimination. Performance comparisons with some state-of-the-art algorithms illustrate that the proposed video hashing outperforms the compared algorithms in classification in terms of receiver operating characteristic results. 相似文献
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Video retrieval methods have been developed for a single query. Multi-query video retrieval problem has not been investigated yet. In this study, an efficient and fast multi-query video retrieval framework is developed. Query videos are assumed to be related to more than one semantic. The framework supports an arbitrary number of video queries. The method is built upon using binary video hash codes. As a result, it is fast and requires a lower storage space. Database and query hash codes are generated by a deep hashing method that not only generates hash codes but also predicts query labels when they are chosen outside the database. The retrieval is based on the Pareto front multi-objective optimization method. Re-ranking performed on the retrieved videos by using non-binary deep features increases the retrieval accuracy considerably. Simulations carried out on two multi-label video databases show that the proposed method is efficient and fast in terms of retrieval accuracy and time. 相似文献
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散列算法已经被广泛应用于视频数据的索引。然而,当前大多数视频散列方法将视频看成是多个独立帧的简单集合,通过综合帧的索引来对每个视频编制索引,在设计散列函数时往往忽略了视频的结构信息。首先将视频散列问题建模为结构正规化经验损失的最小化问题。然后提出一种有监管算法,通过利用结构学习方法来设计高效的散列函数。其中,结构正规化利用了出现于视频帧(与相同的语义类别存在关联)中的常见局部视觉模式,同时对来自同一视频的后续帧保持时域一致性。证明了通过使用加速近端梯度(APG)法可有效求解最小化目标问题。最后,基于两个大规模基准数据集展开全面实验(150 000个视频片断,1 200万帧),实验结果证明了该方法性能优于当前其他算法。 相似文献
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Azhar Hadmi William Puech Brahim Ait Es Said Abdellah Ait Ouahman 《Signal Processing: Image Communication》2013,28(8):929-948
Perceptual hashing is conventionally used for content identification and authentication. It has applications in database content search, watermarking and image retrieval. Most countermeasures proposed in the literature generally focus on the feature extraction stage to get robust features to authenticate the image, but few studies address the perceptual hashing security achieved by a cryptographic module. When a cryptographic module is employed [1], additional information must be sent to adjust the quantization step. In the perceptual hashing field, we believe that a perceptual hashing system must be robust, secure and generate a final perceptual hash of fixed length. This kind of system should send only the final perceptual hash to the receiver via a secure channel without sending any additional information that would increase the storage space cost and decrease the security. For all of these reasons, in this paper, we propose a theoretical analysis of full perceptual hashing systems that use a quantization module followed by a crypto-compression module. The proposed theoretical analysis is based on a study of the behavior of the extracted features in response to content-preserving/content-changing manipulations that are modeled by Gaussian noise. We then introduce a proposed perceptual hashing scheme based on this theoretical analysis. Finally, several experiments are conducted to validate our approach, by applying Gaussian noise, JPEG compression and low-pass filtering. 相似文献
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针对现有多角度人脸图像相互转化算法存在复杂度高、运算量大、重建结果中头发、脸部轮廓部位比较模糊的问题,提出一种利用局部性嵌入法(LLE)进行重建的多角度人脸图像相互转化算法.将人脸特定角度空间的重建系数运用到目标角度空间,在权值求取时运用局部线性嵌入非线性降维算法,并将算法中的局部协方差矩阵进行大常数对角加载.对比实验结果表明,该算法简单,计算速度快,转化后图像质量高,并且在头发和人脸边缘部分合成效果明显优于现有算法. 相似文献
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针对非线性系统故障诊断难以解决的问题,提出了一种基于扩展局部线性嵌入映射(Locally Linear Embedding,LLE)的故障诊断方法.通过引入切空间距离代替欧氏距离,可以更加科学的满足算法近邻点局部线性的要求,从而可以更好的保留原始数据的局部流形特征.另外,将故障状态与高维空间分布结合起来,通过确定数据点在空间超球内的分布完成故障的检测,在这个过程中将超球的确定与LLE算法中基于核函数的样本外数据扩展相结合,减少了计算量,提高了算法的实时性,从而为复杂非线性系统的故障诊断提供了一种新的有效的方法. 相似文献
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Jie Wei 《IEEE transactions on image processing》2005,14(5):662-673
To achieve video understanding, it is of utmost practical importance to classify videos according to its spatial and temporal features in an efficient and effective manner. It still remains, however, largely an elusive task. In still-image analysis, thanks to the great efforts made by many researchers, a broad spectrum of methods have been developed with great success, especially the ones based on eigen analysis due to its efficacy. In this paper, inspired by the impressive performance achieved by this framework, we will develop a content-based video classification method based on three-dimensional (3-D) eigen analysis. Unlike most other video understanding schemes where the spatial and temporal contents play different roles in the processing, this new method treats a video as a solid within a 3-D Euclidean space and can, thus, naturally take advantage of the spatial and temporal contents existing in videos. After computing the eigen values and corresponding eigen vectors of the autocorrelation matrix for each small 3-D macroblock, different labels are assigned regarding its spatial/temporal natures based on the behavioral properties of the eigen values and eigen vectors. Extensive empirical studies have suggested encouraging performance for the use of this eigen analysis-based video classification method. 相似文献