基于相机成像特性的数字图像真伪鉴定
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摘要
新闻图片造假案例层出不穷，严重危害社会稳定。如何在未知原始图像情况下对图像内容真伪进行鉴定成为近年来媒体安全领域的研究热点。现有被动图像取证方法种类繁多，不胜枚举，按其原理大体可分为三类：基于约束理论的内容鉴定、基于痕迹学的内容鉴定和基于内部指纹的来源鉴定。本文分别从相机透视约束、噪声等级函数约束、线性对比度增强痕迹和图像复制-粘贴痕迹等多个视点对图像内容真伪鉴定展开研究，取得的创新成果概括如下：
1.基于透视约束的图像拼接检测。近大远小是相机成像的基本透视特性。篡改者在图像中插入一个对象时，很难确定适当的物体成像高度使其服从透视约束关系。在不考虑相机上下倾角情况下，证明了图像中物体实际高度仅与其所在参考平面灭线（vanishing line）、物体在图像中的坐标位置、相机实际高度这三个量有关，而与相机内部参数无关。针对防伪取证，得出图像中两可疑物体实际高度比仅取决于参考平面灭线和物体坐标的结论，根据此结论提出了对不满足透视约束条件的插入对象的检测方法。实验表明该方法对图像压缩和下采样具有很强的稳健性。
2.基于噪声等级函数不一致性的图像拼接检测。现有基于噪声不一致性取证方法多以高斯白噪声假设为前提，而在实际相机中传感器产生的噪声往往服从更复杂的分布。本文假设局部噪声标准差是图像局部亮度的函数，称之为噪声等级函数。现有用于去噪的噪声等级函数估计方法并不适合取证应用，存在样本集不完备和测量精度受图像内容影响较大的问题。通过推导噪声等级函数与相机响应函数之间的形状约束关系，提出了利用相机响应函数形状对噪声等级函数形状进行约束的联合估计方法。利用图像边缘区和非边缘区样本构造贝叶斯后验概率最大化模型，使噪声等级函数估计和相机响应函数估计同时达到最优。在此基础上提出一类取证算法，通过检测图像中局部区域块的噪声等级不一致性来判断该块是否来自其他图像。
3.对线性对比度增强操作的检测和映射函数系数估计。线性函数是最基本的对比度增强映射函数。由于映射函数的斜率恒定不变，因此图像中直方图会产生周期性梳状效应。本文提出直方图频谱尖峰能量分析方法以检测此种效应，另外还得出分段线性对比度增强中，映射折线的斜率与直方图幅度谱峰值所在频率间的对应关系。以三折线对比度增强映射函数为例，实现了分段线性映射函数的参数估计。
4.基于非负矩阵分解的稳健性图像复制-粘贴操作检测。图像的复制-粘贴操作是指篡改者复制图像部分区域，将它粘贴到本图像的其他区域。本文提出基于块特征匹配的检测方法。用非负矩阵分解得到图像特征，将分解得到的系数二值化，通过计算汉明距离进一步降低匹配复杂度。在保证足够稳健性的前提下，所提出的方法相对于现有基于特征系数相关性的匹配方法具有复杂度低，运算效率高的特点。该方法可抵抗滤波、压缩、低倍率缩放等操作。
本论文提出的方法对于图像被动取证提供了几种有效手段。随着图像处理工具的发展，篡改技巧也不断改进和翻新，使检测的难度更高。进一步完善和提高图像取证技术是一项具有挑战性的长期任务。
News photo forgery scandals emerged continuously in recent years, and thesefake photos can mislead the public and cause serious social harm. How to detectimage forgery without any prior knowledge, which is defined as passive imageforensic techniques, is a new and hot topic for multimedia security researches. Thereare a variety of existing forensic methods, which can be roughly categorized into threegroups: constraints based image content authentication methods, traces based imageforgery detection methods and intrinsic fingerprint based image source identificationmethods. In this dissertation, we mainly focus on identifying image forgery usingperspective constraints and noise feature inconsistency, and detecting the tamperingtraces left by piecewise linear contrast enhancement and image copy-movemanipulations. The contributions of this dissertation are listed as follows:
1. Propose an image splicing detection method using perspective constraints
In visual perception, distant objects appear smaller than those close to theobserver. To insert one object into an image, due to the interference of perspectiveeffects, the forger may not control the proper size of the foreign object in this imageeasily. When neglecting camera tilt and roll, via derivation, we demonstrate that theheight of any object sitting on a reference plane can be uniquely decided by thevanishing line of the reference plane, the pixel coordinates of this object in the imageand the height of camera. Furthermore, we develop this characteristic into imageforensics. To eliminate the dependence on camera height, we estimate the height ratioof two objects both resting on the reference plane and evaluate it with reference ratio.Since it do not need any prior knowledge of camera parameters, the proposed perspective constraints based method can be widely used for forensic applications.The experimental results demonstrate the efficacy of the method, even though theimages are down-sampled and high-ratio compressed.
2. Develop a MAP based noise level function estimation method and apply it intoimage splicing detection
Existing noise inconsistency based image forensic methods are all with theassumption of man-made white noise. However, this assumption does not hold inmost practical sensor noise generation process. In this dissertation, the standarddeviation of noise distribution is modeled as a function with respect to image intensity,and this function is defined as noise level function (NLF). In comparison todenoising-oriented methods, incomplete sample set and unstable statistic measuringare both major challenges for application in forensics. After exposing the closerelationship between NLF and camera response function (CRF), we fit the curve ofNLF with the constraints imposed by the shape of CRF. Then we formulate aBayesian maximum a posteriori (MAP) framework to optimize the NLF estimation.Besides, we design a novel splicing forgery detection method based on the noise levelinconsistency maintaining in each image block pair from different origins.
3. Propose a method to detect the trace of linear contrast enhancement andestimate the mapping parameters simultaneously
Linear contrast enhancement is one of the common contrast modificationapproaches. Owning to the constant slope in linear mapping function, periodiccomb-like artifacts appear in image histogram. We exploit histogram frequencyanalysis method to expose this artifact. Also based on this observation, a parametersestimation approach is proposed. The peak frequency in spectrum has a strongrelationship with the slope of mapping function for estimation. To exemplify theefficacy of the proposed method, a three piecewise linear mapping function issupposed for estimation.
4. Propose an approach to detect image copy-move forgery via non-negativematrix factorization and lexicographic sorting matching
A manipulation duplicating one region of the image and pasting to another in thesame image is known as copy-move forgery. The proposed method, which belongs tothe block-feature matching category, extracts features from each block usingnon-negative matrix factorization. In order to further reduce the matching complexity,the feature coefficients are quantized to be binary and difference between each blockpair are measured by Hamming distance. A lexicographic sorting is also introduced toeliminate the redundant matchings. Low extraction complexity and high matchingefficiency are both the main advantages of the proposed method, the effectiveness ofwhich to conter filtering, compression and minor rescaling is demonstrated inexperimental results.
1.基于透视约束的图像拼接检测。近大远小是相机成像的基本透视特性。篡改者在图像中插入一个对象时，很难确定适当的物体成像高度使其服从透视约束关系。在不考虑相机上下倾角情况下，证明了图像中物体实际高度仅与其所在参考平面灭线（vanishing line）、物体在图像中的坐标位置、相机实际高度这三个量有关，而与相机内部参数无关。针对防伪取证，得出图像中两可疑物体实际高度比仅取决于参考平面灭线和物体坐标的结论，根据此结论提出了对不满足透视约束条件的插入对象的检测方法。实验表明该方法对图像压缩和下采样具有很强的稳健性。
2.基于噪声等级函数不一致性的图像拼接检测。现有基于噪声不一致性取证方法多以高斯白噪声假设为前提，而在实际相机中传感器产生的噪声往往服从更复杂的分布。本文假设局部噪声标准差是图像局部亮度的函数，称之为噪声等级函数。现有用于去噪的噪声等级函数估计方法并不适合取证应用，存在样本集不完备和测量精度受图像内容影响较大的问题。通过推导噪声等级函数与相机响应函数之间的形状约束关系，提出了利用相机响应函数形状对噪声等级函数形状进行约束的联合估计方法。利用图像边缘区和非边缘区样本构造贝叶斯后验概率最大化模型，使噪声等级函数估计和相机响应函数估计同时达到最优。在此基础上提出一类取证算法，通过检测图像中局部区域块的噪声等级不一致性来判断该块是否来自其他图像。
3.对线性对比度增强操作的检测和映射函数系数估计。线性函数是最基本的对比度增强映射函数。由于映射函数的斜率恒定不变，因此图像中直方图会产生周期性梳状效应。本文提出直方图频谱尖峰能量分析方法以检测此种效应，另外还得出分段线性对比度增强中，映射折线的斜率与直方图幅度谱峰值所在频率间的对应关系。以三折线对比度增强映射函数为例，实现了分段线性映射函数的参数估计。
4.基于非负矩阵分解的稳健性图像复制-粘贴操作检测。图像的复制-粘贴操作是指篡改者复制图像部分区域，将它粘贴到本图像的其他区域。本文提出基于块特征匹配的检测方法。用非负矩阵分解得到图像特征，将分解得到的系数二值化，通过计算汉明距离进一步降低匹配复杂度。在保证足够稳健性的前提下，所提出的方法相对于现有基于特征系数相关性的匹配方法具有复杂度低，运算效率高的特点。该方法可抵抗滤波、压缩、低倍率缩放等操作。
本论文提出的方法对于图像被动取证提供了几种有效手段。随着图像处理工具的发展，篡改技巧也不断改进和翻新，使检测的难度更高。进一步完善和提高图像取证技术是一项具有挑战性的长期任务。
News photo forgery scandals emerged continuously in recent years, and thesefake photos can mislead the public and cause serious social harm. How to detectimage forgery without any prior knowledge, which is defined as passive imageforensic techniques, is a new and hot topic for multimedia security researches. Thereare a variety of existing forensic methods, which can be roughly categorized into threegroups: constraints based image content authentication methods, traces based imageforgery detection methods and intrinsic fingerprint based image source identificationmethods. In this dissertation, we mainly focus on identifying image forgery usingperspective constraints and noise feature inconsistency, and detecting the tamperingtraces left by piecewise linear contrast enhancement and image copy-movemanipulations. The contributions of this dissertation are listed as follows:
1. Propose an image splicing detection method using perspective constraints
In visual perception, distant objects appear smaller than those close to theobserver. To insert one object into an image, due to the interference of perspectiveeffects, the forger may not control the proper size of the foreign object in this imageeasily. When neglecting camera tilt and roll, via derivation, we demonstrate that theheight of any object sitting on a reference plane can be uniquely decided by thevanishing line of the reference plane, the pixel coordinates of this object in the imageand the height of camera. Furthermore, we develop this characteristic into imageforensics. To eliminate the dependence on camera height, we estimate the height ratioof two objects both resting on the reference plane and evaluate it with reference ratio.Since it do not need any prior knowledge of camera parameters, the proposed perspective constraints based method can be widely used for forensic applications.The experimental results demonstrate the efficacy of the method, even though theimages are down-sampled and high-ratio compressed.
2. Develop a MAP based noise level function estimation method and apply it intoimage splicing detection
Existing noise inconsistency based image forensic methods are all with theassumption of man-made white noise. However, this assumption does not hold inmost practical sensor noise generation process. In this dissertation, the standarddeviation of noise distribution is modeled as a function with respect to image intensity,and this function is defined as noise level function (NLF). In comparison todenoising-oriented methods, incomplete sample set and unstable statistic measuringare both major challenges for application in forensics. After exposing the closerelationship between NLF and camera response function (CRF), we fit the curve ofNLF with the constraints imposed by the shape of CRF. Then we formulate aBayesian maximum a posteriori (MAP) framework to optimize the NLF estimation.Besides, we design a novel splicing forgery detection method based on the noise levelinconsistency maintaining in each image block pair from different origins.
3. Propose a method to detect the trace of linear contrast enhancement andestimate the mapping parameters simultaneously
Linear contrast enhancement is one of the common contrast modificationapproaches. Owning to the constant slope in linear mapping function, periodiccomb-like artifacts appear in image histogram. We exploit histogram frequencyanalysis method to expose this artifact. Also based on this observation, a parametersestimation approach is proposed. The peak frequency in spectrum has a strongrelationship with the slope of mapping function for estimation. To exemplify theefficacy of the proposed method, a three piecewise linear mapping function issupposed for estimation.
4. Propose an approach to detect image copy-move forgery via non-negativematrix factorization and lexicographic sorting matching
A manipulation duplicating one region of the image and pasting to another in thesame image is known as copy-move forgery. The proposed method, which belongs tothe block-feature matching category, extracts features from each block usingnon-negative matrix factorization. In order to further reduce the matching complexity,the feature coefficients are quantized to be binary and difference between each blockpair are measured by Hamming distance. A lexicographic sorting is also introduced toeliminate the redundant matchings. Low extraction complexity and high matchingefficiency are both the main advantages of the proposed method, the effectiveness ofwhich to conter filtering, compression and minor rescaling is demonstrated inexperimental results.
引文
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