Malicious inter-frame video tampering detection in MPEG videos using time and spatial domain analysis of quantization effects

In this paper, a new algorithm is proposed for forgery detection in MPEG videos using spatial and time domain analysis of quantization effect on DCT coefficients of I and residual errors of P frames. The proposed algorithm consists of three modules, including double compression detection, malicious tampering detection and decision fusion. Double compression detection module employs spatial domain analysis using first significant digit distribution of DCT coefficients in I frames to detect single and double compressed videos using an SVM classifier. Double compression does not necessarily imply the existence of malignant tampering in the video. Therefore, malicious tampering detection module utilizes time domain analysis of quantization effect on residual errors of P frames to identify malicious inter-frame forgery comprising frame insertion or deletion. Finally, decision fusion module is used to classify input videos into three categories, including single compressed videos, double compressed videos without malicious tampering and double compressed videos with malicious tampering. The experimental results and the comparison of the results of the proposed method with those of other methods show the efficiency of the proposed algorithm.     

基于块边缘模式的图像内容描述符

本文提出一种有效的基于从图像压缩域提取的块边缘模式的内容描述符,它特别适用于JPEG压缩图像或MPEG压缩视频.该图像内容描述符由三种块边缘模式的游程编码直方图构成.大量的实验结果证明,与现行的类似算法相比,本文提出的算法在进行图像检索时,具有更高的平均查准率和查全率.     

MPEG压缩域关键帧提取的研究

提出了一种基于MPEG压缩域关键帧的提取方法.首先对MPEG压缩域中实现I帧的提取,然后利用I帧的特征8×8块的DC系数,计算相邻I帧对应位置的8×8块的DC系数相似性度量,进而实现镜头的判断,最后利用P帧宏块类型提取关键帧.由于处理过程是直接从MPEG的压缩视频提取,不需要对其完全解压,所以计算复杂度低,提高了提取速...     

基于DCT压缩域的图象字符定位

为了能够利用图象中所含的文字信息来进行图象的快速高效浏览检查，其中，快速字符定位是很重要的工作，为此设计了一种直接在图象压缩域中进行字符定位的方法，该方法主要是利用图象中字符纹理所具有的方向性特点，首先直接在DCT域中提取字符的横向、竖向、斜向纹理的方向信息，然后根据各自的阈值把字符区域从图象背景中分割出来，在处理过程中，用形态滤波的方法可有效地消除噪音点，该算法可直接处理JPEG、MPEG等以DCT为编码基础的压缩数据，仅需少量的解码过程（Huffman解码）即可完成字符定位，因此要处理的数据量较少，用该算法既提高了处理速度，又减少了对计算机资源的需求，试验结果表明，此方法具有较高的准确率。     

Video text detection and localization in intra-frames of H.264/AVC compressed video

Video texts are closely related to the video content. The video text information can facilitate content based video analysis, indexing and retrieval. Video sequences are usually compressed before storage and transmission. A basic step of text-based applications is text detection and localization. In this paper, an overlaid text detection and localization method is proposed for H.264/AVC compressed videos by using the integer discrete cosine transform (DCT) coefficients of intra-frames. The main contributions of this paper are in the following two aspects: 1) coarse text blocks detection using block sizes and quantization parameters adaptive thresholds; 2) text line localization according to the characteristics of text in intra frames of H.264/AVC compressed domain. Comparisons are made with the pixel domain based text detection method for the H.264/AVC compressed video. Text detection results on five H.264/AVC video sequences under various qualities show the effectiveness of the proposed method.     

一种压缩域中基于镜头的关键帧提取改进算法*

关键帧提取技术是基于内容视频检索的基础。针对压缩视频序列提出一种基于镜头的关键帧提取改进算法。其核心是根据压缩视频序列的编码特点,只需要对其进行部分解码,利用I帧信息的直流分量信息构造DC缩微图,并结合图像帧不同区域DC信息的重要程度差异进行相似性度量,进而实现关键帧提取。实验证明,该算法较之传统算法,在查全率和检索时间两项指标上均有显著改善,尤其适用于新闻纪录片、电影片等局部运动较为剧烈的视频序列。     

Compressed domain content based retrieval using H.264 DC-pictures

A fast and simple method for content based retrieval using the DC-pictures of H.264 coded video without full decompression is presented. Compressed domain retrieval is very desirable for content analysis and retrieval of compressed image and video. Even though, DC-pictures are among the most widely used compressed domain indexing and retrieval methods in pre H.264 coded videos, they are not generally used in the H.264 coded video. This is due to two main facts, first, the I-frame in the H.264 standard are spatially predicatively coded and second, the H.264 standard employs Integer Discrete Cosine Transform. In this paper we have applied color histogram indexing method on the DC-pictures derived from H.264 coded I-frames. Since the method is based on independent I-frame coded pictures, it can be used either for video analysis of H.264 coded videos, or image retrieval of the I-frame based coded images such as advanced image coding. The retrieval performance of the proposed algorithm is compared with that the fully decoded images. Simulation results indicate that the performance of the proposed method is very close to the fully decompressed image systems. Moreover the proposed method has much lower computational load.     

视频压缩流简化帧处理中若干问题研究

数据压缩技术主要用于减小视频数据的大小,以满足存储和传输的需要,但现有的图象处理技术必须先将视频压缩流完全解压后才能进行处理,本文讨论了不需要完全解压缩或仅需很小的解压就能直接对视流进行处理的方法,如ＭＰＥＧ压缩视频流中Ｐ帧和Ｂ帧以及常用的压缩域处理方法以及存在的问题,最后证明了在半象素运动矢量情况下ＭＰＥＧ简化帧抽取的准确性问题,视频压缩流在压缩域处理的特点是不仅减少了解压缩所需要的计算时间,而     

基于DCT压缩的JPEG图像的快速检索

提出了一种基于离散余弦变换(DCT)压缩的JPEC图像的检索方法。该方法利用JPEG图像数据在DCT压缩域的特性,直接提取特征,而且只需要对JPEC进行部分熵解码。在加速了图像检索的过程的同时也保证了检索结果的精确性,并且具有一定的鲁棒性。     

基于总变分的MPEG解码算法

针对低比特MPEG图像序列出现的压缩痕迹,提出一种后处理正则化方法进行MPEG解码。首先由自适应量化得到一个原始视频DCT系数的量化区间,重建的视频序列投影到此区间内,其次视频是连续的静止图像,得到耦合时间维度和分离时间维度的两种总变分模型,最后利用经典的原-对偶算法求解提出来的凸优化模型,得到后处理MPEG解码视频序列。实验结果表明,总变分正则化函数能够一定程度上减轻压缩痕迹,提高解码视频的质量。     

Fast scene change detection using direct feature extraction fromMPEG compressed videos

In order to process video data efficiently, a video segmentation technique through scene change detection must be required. This is a fundamental operation used in many digital video applications such as digital libraries, video on demand (VOD), etc. Many of these advanced video applications require manipulations of compressed video signals. So, the scene change detection process is achieved by analyzing the video directly in the compressed domain, thereby avoiding the overhead of decompressing video into individual frames in the pixel domain. In this paper, we propose a fast scene change detection algorithm using direct feature extraction from MPEG compressed videos, and evaluate this technique using sample video data, First, we derive binary edge maps from the AC coefficients in blocks which were discrete cosine transformed. Second, we measure edge orientation, strength and offset using correlation between the AC coefficients in the derived binary edge maps. Finally, we match two consecutive frames using these two features (edge orientation and strength). This process was made possible by a new mathematical formulation for deriving the edge information directly from the discrete cosine transform (DCT) coefficients. We have shown that the proposed algorithm is faster or more accurate than the previously known scene change detection algorithms     

基于宏块运动信息的镜头边界检测

镜头边界检测是视频处理与检索中最重要的第一步。对视频流直接在压缩域中部分解压I帧,提取其DC图像的特征,利用连续I帧的DC图像的特征差异粗略定位镜头的边界,再根据压缩域中P、B帧的各种类型的宏块数量变化精确定位镜头边界。实验结果表明,本算法能高效而精确地对突变镜头和渐变镜头进行检测,弥补了压缩域中镜头定位精确性不高的缺点。     

General methods for L/M-fold resizing of compressed images using lapped transforms

Two general methods are proposed for the arbitrary L/M-fold resizing of compressed images using lapped transforms. These methods provide general resizing frameworks in the transform domain. In order to analyse the image size conversion technique using lapped transforms, the impulse responses and frequency responses for the overall system are derived and analysed. This theoretical analysis shows that the image resizing in the lapped transform domain provides much better characteristics than the conventional image resizing in the discrete cosine transform (DCT) domain. Specifically, by using lapped transforms, the proposed method reduces the blocking effect to a very low level for images which are compressed at low bit rates, since two neighbouring DCT blocks are used in the conversion process, instead of processing each block independently.     

Mining Appearance Models Directly From Compressed Video

In this paper, we propose an approach for learning appearance models of moving objects directly from compressed video. The appearance of a moving object changes dynamically in video due to varying object poses, lighting conditions, and partial occlusions. Efficiently mining the appearance models of objects is a crucial and challenging technology to support content-based video coding, clustering, indexing, and retrieval at the object level. The proposed approach learns the appearance models of moving objects in the spatial-temporal dimension of video data by taking advantage of the MPEG video compression format. It detects a moving object and recovers the trajectory of each macroblock covered by the object using the motion vector present in the compressed stream. The appearances are then reconstructed in the DCT domain along the object's trajectory, and modeled as a mixture of Gaussians (MoG) using DCT coefficients. We prove that, under certain assumptions, the MoG model learned from the DCT domain can achieve pixel-level accuracy when transformed back to the spatial domain, and has a better band-selectivity compared to the MoG model learned in the spatial domain. We finally cluster the MoG models to merge the appearance models of the same object together for object-level content analysis.     

基于Retinex理论的压缩域图像增强方法研究

针对现有压缩域图像增强算法在提高图像对比度时,存在不能很好地增强图像细节及保持色彩信息的局限性,提出一种新的基于Retinex理论的DCT压缩域图像增强算法.该算法以Retinex理论为基础,将DCT系数分为入射分量(DC系数)和反射分量(AC系数),通过对DC系数进行动态范围调整,对AC系数进行细节增强调整,并使用阈...     

Multivariate image similarity in the compressed domain using statistical graph matching

We address the problem of image similarity in the compressed domain, using a multivariate statistical test for comparing color distributions. Our approach is based on the multivariate Wald-Wolfowitz test, a nonparametric test that assesses the commonality between two different sets of multivariate observations. Using some pre-selected feature attributes, the similarity measure provides a comprehensive estimate of the match between different images based on graph theory and the notion of minimal spanning tree (MST). Feature extraction is directly provided from the JPEG discrete cosine transform (DCT) domain, without involving full decompression or inverse DCT. Based on the zig-zag scheme, a novel selection technique is introduced that guarantees image's enhanced invariance to geometric transformations. To demonstrate the performance of the proposed method, the application on a diverse collection of images has been systematically studied in a query-by-example image retrieval task. Experimental results show that a powerful measure of similarity between compressed images can emerge from the statistical comparison of their pattern representations.     

一种基于梯度模型的MPEG压缩域的运动对象分割算法

视频数据大都是经过压缩域的形式存储和传输的,且直接在压缩域进行视频对象分割无需运动估计等复杂的计算,速度较快。本文提出了一种基于梯度模型的MPEG压缩域的运动对象分割算法。首先利用DCT(AC[1]和AC[8])系数获得所有物体的边缘,然后综合在累积运动矢量基础上得到的边缘运动信息,从而获得感兴趣运动物体的边缘。仿真实验结果表明,它可以取得满意的分割质量。     

基于数据隐藏的图像检索系统

本文提出一种新的图像检索系统,采用数据隐藏算法把图像的标注信息和特征信息嵌入压缩域图像中,用于快速检索。由于DCT在图像压缩中得到了广泛的应用,本文分析了基于DCT的JPEG图像格式编码流程,实现了一种基于JPEG压缩的数据隐藏算法。实验结果表明,该算法未引起图像质量明显下降,可嵌入较多数据。