基于LOCP特征的JPEG2000二次压缩检测

JPEG2000二次压缩检测,即对图片进行二次JPEG2000压缩的检测,对于分析图像篡改、隐写等有重要价值。文中分析了现有的JPEG2000二次压缩检测算法的优势,结合LOCP特征,提出了一种改进的JPEG2000二次压缩检测算法。该算法对对象图片的高频成分提取LOCP特征,并用支持向量机SVM分类器进行训练和检测。在哥伦比亚大学篡改检测图像数据集上的实验显示,提出的JPEG2000二次压缩检测算法较原有算法有较大提升,并获得了TODO的检测率。     

图像重采样检测

图像的重采样篡改检测和JPEG双重压缩的篡改检测都是图像篡改取证的重要方法.大多数重采样篡改检测都会忽略JPEG压缩对图像的影响,而文中提出的方法主要是利用图像经过重采样和JPEG压缩之后的周期性、图像的自然统计特征对重采样图像进行检测,首先提取出可以区分原图像和重采样图像的重采样因子和JPEG压缩因子,然后提取图像的4个统计特征,最后将6个因子组合成特征向量,利用支持向量机对其进行训练和分类.实验证明,该算法对于缩放因子小于1的图像和原图像都有较好的检测率.     

基于JPEG双量化特性的彩色伪造图像盲检测

现有的盲检测方法主要针对灰度图像和未压缩图像,很多算法都不能有效地检测彩色压缩伪造图像。本文提出了一种利用JPEG双量化失真特性实现彩色压缩伪造图像盲检测的方法。通过分析伪造图像的制作过程,可知由多幅JPEG图像拼接成的高质量彩色伪造图像中篡改区域和背景区域经历的双量化过程不同。根据这一特性,本文首先使用背景区域的初始量化表估计值对待检测图像进行再压缩处理,定义再压缩后图像各颜色分量的失真函数;然后根据各失真函数在图像不同区域的取值,由各颜色分量分别确定篡改区域;最后综合彩色图像各颜色分量的检测结果,最终识别出彩色图像篡改区域的位置和大小。仿真结果表明该方法不但可以有效地识别彩色伪造图像的篡改区域,而且比基于单一颜色分量的检测方法更加准确。      

基于DCT系数双量化映射关系的图像盲取证算法

图像篡改过程会留下一些痕迹破坏自然图像的一致性,为图像的盲取证提供了线索。该文针对篡改过程中的JPEG重压缩操作,根据原始离散余弦变换(DCT)系数与重压缩后DCT系数的映射关系,提出一种新的图像重压缩概率模型来描述重压缩前后DCT系数统计特性的变化,并结合贝叶斯准则,利用后验概率表示JPEG篡改图像中存在的 DQ(Double Quantization)效应,通过后验概率密度图实现篡改区域的定位。实验表明,该方法能够快速并准确实现篡改区域的自动检测和定位,尤其是当第2次压缩因子小于第1次压缩因子时,正确率相对于传统算法有明显的提高。该方法不仅能检测Photoshop等图像编辑软件制作的手工合成篡改图像,同样也适用于图像智能编辑算法如图像修复算法和图像重排算法制作的篡改图像。     

一种基于JPEG压缩的半脆弱水印算法

本文分析了JPEG压缩中的DCT变换和量化过程，根据量化的特性提出了一种半脆弱水印方案，并将水印信息调制为纠错码嵌入JPEG压缩过程的量化系数中，实验证明，此水印方案鲁棒性较强，虚警率低，能较好的检测图像是否被篡改并对篡改定位。     

双重JPEG压缩图像篡改区域检测与定位

对JPEG(joint photographic experts group)图像实施篡改往往会产生双重JPEG(double JPEG,DJPE) 压缩痕迹,分析该痕迹有助于揭示图像压缩历史并实现篡改区域定位。现有算法在图像尺寸较小和质量因子(quality factor,QF) 较低的时候性能不佳,对两个QF的组合情况存在限制。本文提出了一种端到端的混合QF双重JPEG压缩图像取证网络,命名为DJPEGNet。首先,使用预处理层从图像头文件中提取表征压缩历史信息的量化表 (quantization table,Qtable) 特征,将图像从空域转换至DCT(discrete cosine transform)域构造统计直方图特征。然后,将两个特征输入到由深度可分离卷积和残差结构堆叠而成的主体结构,输出二分类结果。最后,使用滑动窗口算法自动定位篡改区域并绘制概率分布图。实验结果表明,在使用不同Qtable集生成的小尺寸数据集上,DJPEGNet所有指标均优于现有最先进的算法,其中ACC提高了1.78%,TPR提升了2.00%,TNR提升了1.60%。     

一种基于人眼对比度敏感视觉特性的图像自适应量化方法

为了提高图像的压缩比和压缩质量,结合人眼对比度敏感视觉特性和图像变换域频谱特征,该文提出一种自适应量化表的构建方法。并将该表代替JPEG中的量化表,且按照JPEG的编码算法对3幅不同的彩色图像进行了压缩仿真实验验证,同时与JPEG压缩作对比分析。实验结果表明:与JPEG压缩方法相比,在相同的压缩比下,采用自适应量化压缩后,3幅解压彩色图像的SSIM和PSNR值分别平均提高了1.67%和4.96%。表明该文提出的结合人眼视觉特性的自适应量化是一种较好的、有实用价值的量化方法。     

JPEG图像被动取证研究进展综述

数字图像被动取证是利用图像的固有属性对其真实性认证、拼接区域定位及篡改历史分析的技术。由于大多数图像都需要进行JPEG压缩以便存储和传输，基于JPEG格式的数字图像被动取证越来越受到关注。为了更加全面地对现有取证方法进行梳理与归纳，本文着重对JPEG图像相关的取证技术进行介绍，详细论述了双重JPEG压缩检测、量化矩阵估计和拼接检测与定位方法中的关键技术，分析现有方法存在的问题与面临的困难，并对未来发展方向进行展望。      

基于JPEG压缩不变量和数字水印的图像认证方法

提出一种抗JPEG压缩的图像认证算法。根据图像不同块中位置相同的DCT系数之间的大小关系在JPEG压缩之后几乎没有发生变化这一性质,对图像进行分析生成特征编码,并将特征编码加密后以水印方式嵌入图像。认证时只需将待测图像的特征编码与从中抽取出的解密水印进行比较,利用篡改矩阵鉴别是否有内容被篡改,并给出具体的篡改位置。实验结果表明,该算法有很好的抗JPEG压缩性能,并可有效地检测出恶意篡改及其发生的位置。     

利用Photoshop中高斯模糊进行篡改的取证方法北大核心

经过篡改伪造后的数字图像,几乎都需要使用模糊操作对篡改伪造边缘进行润饰处理,以实现篡改区域的不可见性,因此对模糊润饰操作的检测可以作为篡改伪造取证的重要依据之一。通过对JPEG图像中DCT系数块内相关性的分析,得到二维高斯分布描述量化DCT系数的联合概率密度分布,因此,通过提取高斯模糊篡改的图像DCT系数的联合概率密度特征与未篡改图像的DCT系数的联合概率密度进行对比检测取证。实验表明,该方法能够有效地检测经过Photoshop高斯模糊篡改的数字图像。     

基于条件共生概率矩阵的移位JPEG双压缩检测

针对合成JPEG图像的小区域移位JPEG双压缩(SD-JPEG压缩)篡改问题,提出一种基于条件共生概率矩阵(CCPM)的SD-JPEG压缩篡改检测算法。为了减小图像内容的影响,增强SD-JPEG压缩效应,首先对JPEG量化的离散余弦变换(DCT)系数的幅度矩阵进行水平、垂直、主对角和副对角4个方向差分和阈值化处理,然后使用CCPM对这4个阈值化的差分矩阵进行建模,选取CCPM的元素作为特征数据,并用主分量分析(PCA)对其降维处理,最后通过支持向量机(SVM)技术判决图像块是否经过SD-JPEG压缩。实验结果验证了本文算法的有效性。     

Content Authentication Based on JPEG-to-JPEG Watermarking

A content authentication technique based on JPEG-to-JPEG watermarking is proposed in this paper. In this technique, each 8x8 block in a JPEG compressed image is first processed by entropy decoding, and then the quantized discrete cosine transform （DCT） is applied to generate DCT coefficients： one DC coefficient and 63 AC coefficients in frequency coefficients. The DCT AC coefficients are used to form zero planes in which the watermark is embedded by a chaotic map. In this way, the watermark information is embedded into JPEG compressed domain, and the output watermarked image is still a JPEG format. The proposed method is especially applicable to content authentication of JPEG image since the quantized coefficients are modified for embedding the watermark and the chaotic system possesses an important property with the high sensitivity on initial values. Experimental results show that the tamper regions are localized accurately when the watermarked JPEG image is maliciously tampered.     

Content Authentication Based on JPEG-to-JPEG Watermarking

A content authentication technique based on JPEG-to-JPEG watermarking is proposed in this paper. In this technique, each 88 block in a JPEG compressed image is first processed by entropy decoding, and then the quantized discrete cosine transform (DCT) is applied to generate DCT coefficients: one DC coefficient and 63 AC coefficients in frequency coefficients. The DCT AC coefficients are used to form zero planes in which the watermark is embedded by a chaotic map. In this way, the watermark information is embedded into JPEG compressed domain, and the output watermarked image is still a JPEG format. The proposed method is especially applicable to content authentication of JPEG image since the quantized coefficients are modified for embedding the watermark and the chaotic system possesses an important property with the high sensitivity on initial values. Experimental results show that the tamper regions are localized accurately when the watermarked JPEG image is maliciously tampered.     

Detection and localization of forgery using statistics of DCT and Fourier components

In this paper, we present a comprehensive approach for investigating JPEG compressed test images, suspected of being tampered either by splicing or copy-move forgery (cmf). In JPEG compression, the image plane is divided into non-overlapping blocks of size 8 × 8 pixels. A unified approach based on block-processing of JPEG image is proposed to identify whether the image is authentic/forged and subsequently localize the tampered region in forged images. In the initial step, doubly stochastic model (dsm) of block-wise quantized discrete cosine transform (DCT) coefficients is exploited to segregate authentic and forged JPEG images from a standard dataset (CASIA). The scheme is capable of identifying both the types of forged images, spliced as well as copy-moved. Once the presence of tampering is detected, the next step is to localize the forged region according to the type of forgery. In case of spliced JPEG images, the tampered region is localized using block-wise correlation maps of dequantized DCT coefficients and its recompressed version at different quality factors. The scheme is able to identify the spliced region in images tampered by pasting uncompressed or JPEG image patch on a JPEG image or vice versa, with all possible combinations of quality factors. Alternatively, in the case of copy-move forgery, the duplication regions are identified using highly localized phase congruency features of each block. Experimental results are presented to consolidate the theoretical concept of the proposed technique and the performance is compared with the already existing state of art methods.     

Blind method for rescaling detection and rescale factor estimation in digital images using periodic properties of interpolation

Availability of the powerful image editing softwares and advancement in digital cameras has given rise to large amount of manipulated images without any traces of tampering, generating a great demand for automatic forgery detection algorithms in order to determine its authenticity. When altering an image like copy–paste or splicing to conceal traces of tampering, it is often necessary to resize the pasted portion of the image. The resampling operation may highly likely disturb the underlying inconsistency of the pasted portion that can be used to detect the forgery. In this paper, an algorithm is presented that blindly detects global rescaling operation and estimate the rescaling factor based on the autocovariance sequence of zero-crossings of second difference of the tampered image. Experimental results using UCID and USC-SIPI database show the validity of the algorithm under different interpolation schemes. The technique is robust and successfully detects rescaling operation for images that have been subjected to various forms of attacks like JPEG compression and arbitrary cropping. As expected, some degradation in detection accuracy is observed as the JPEG quality factor decreased.     

Image/video spatial scalability in compressed domain

Image/video compression is widely used in various applications with the advent of the Joint Photographic Expert Group (JPEG), Motion Picture Expert Group (MPEG), and H.261 standards. Hence, most visual data are stored in the compressed format. Spatial scalable encoding of visual data has several applications, including browsing visual databases, querying multimedia databases, interactive multimedia communications, etc. We propose two novel techniques, namely, format compatible (FC) discrete cosine transform (DCT) and format modified (FM) DCT to implement image/video spatial scalability directly in the DCT compressed domain. The FC-DCT technique can be used to manipulate the standard bit streams, such as JPEG, MPEG, etc., while the FM-DCT technique can be employed in a variety of applications which require fast processing. In contrast to the traditional spatial-domain techniques, the compressed-domain techniques remove the unnecessary decompression and recompression procedures, thus, they have the advantages of reduced computational complexity and storage requirements. Simulation results demonstrate that the proposed DCT-domain techniques can achieve a comparable performance at a much lower computational complexity compared to the spatial-domain techniques     

针对一类JPEG图像伪造的被动盲取证

图像合成是一种最常见的图像伪造手段。该文针对一类JPEG图像合成伪造,根据篡改区域与非篡改区域块效应的不一致性,提出了一种简单有效的检测算法。首先利用估计的一次压缩质量因子对待检测图像进行裁剪再压缩,然后通过计算压缩前后的失真提取图像的块效应指数映射图,最后采用图像分割的方法实现篡改区域的自动检测与定位。实验结果表明,算法对于各种质量的JPEG图像和较小的篡改区域均能有效检测,当二次压缩与一次压缩的质量因子之差在15以上,虚警率控制在5%以内时,检测率可达93%以上。     

A novel chaos-based fragile watermarking for image tampering detection and self-recovery

In this paper, a novel watermarking approach is proposed to provide enhanced tampering localization and self-recovery. A cross chaotic map is used to confuse the blocks generated by the original image. A sister block embedding scheme is proposed to improve the recovery effect after tampering. Flags and a combination of the most significant bit (MSB) and the least significant bit (LSB) mechanism are applied to improve the tampering detection rate and the defense of attacks. And an optimization scheme is given to make the recovered image have advanced visual effects. Experiment results show that the proposed schemes are more secure and have better effect on tampering detection and recovery even though the tampered area is relatively large.