基于极性复指数变换的图像伪造检测算法

为解决当前图像伪造检测方法在识别复制内容区域时忽略了颜色信息和不同颜色分量之间的相关性,使其对伪造内容的定位与检测准确度不理想的问题,设计了基于改进的加速稳健特征(SURF)描述符与多元极性复指数变换的图像伪造检测算法。引入高斯低通滤波器,对彩色图像完成过滤,以消除噪声,再计算滤波图像的颜色不变性,用其替代SURF描述符中的灰度分量,对SURF方法予以改进,获取新的Hessian矩阵,充分检测彩色图像中的兴趣点;随后,利用这些兴趣点来构建一组连通的Delaunay三角网。基于四元极性复指数变换,充分考虑不同颜色分量之间的相关性,有效提取三角网的局部视觉特征;计算视觉特征之间的欧式距离,根据预设阈值,对三角网实施配准;最后,引入随机样本一致性,剔除错误匹配的三角网,并定义后处理方法,检测出复制伪造区域。测试数据显示：相对已有的复制-粘贴伪造检测方法,在多种几何变换条件下,所提方法具有更高的伪造检测准确性。     

区分来源和目标区域的图像copy-move伪造检测方法

Copy-move是一种常用的图像伪造手段,它通过复制图像的某一区域,移动并粘贴到同一图像的其他位置,达到掩盖重要信息或伪造虚假场景的目的。近年来,为了防止copy-move被用于违法犯罪,copy-move伪造检测技术迅猛发展,在维护社会运行秩序和信息安全方面发挥着积极作用。本文提出一种基于条件生成对抗网络(conditional Generative Adversarial Networks, cGANs)的copy-move伪造检测方法。针对图像copy-move伪造检测,该方法优化设计了cGANs的损失函数,并使用适量的弱监督样本来提升网络性能。不同于目前大部分检测算法,该方法不仅可以定位出图像中的相似区域,还可以有效区分伪造来源区域和伪造目标区域。实验结果表明,本文所提出的方法在检测准确率上显著优于现有方法。      

Copy-move image forgery detection based on Gabor magnitude

With advancement of media editing software, even people who are not image processing experts can easily alter digital images. Various methods of digital image forgery exist, such as image splicing, copy-move forgery, and image retouching. The most common method of tampering with a digital image is copy-move forgery, in which a part of an image is duplicated and used to substitute another part of the same image at a different location. In this paper, we present an efficient and robust method to detect such artifacts. First, the tampered image is segmented into overlapping fixed-size blocks, and the Gabor filter is applied to each block. Thus, the image of Gabor magnitude represents each block. Secondly, statistical features are extracted from the histogram of orientated Gabor magnitude (HOGM) of overlapping blocks, and reduced features are generated for similarity measurement. Finally, feature vectors are sorted lexicographically, and duplicated image blocks are identified by finding similarity block pairs after suitable post-processing. To enhance the algorithm’s robustness, a few parameters are proposed for removing the wrong similar blocks. Experiment results demonstrate the ability of the proposed method to detect multiple examples of copy-move forgery and precisely locate the duplicated regions, even when dealing with images distorted by slight rotation and scaling, JPEG compression, blurring, and brightness adjustment.     

顽健合成图像篡改检测及定位

针对自然图像与高度仿真的计算机生成图像的合成图像篡改检测问题,提出在YCbCr颜色空间基于差分直方图和中心对称局部二进制模式提取图像块颜色和纹理特征的方法,通过训练后验概率支持向量机模型对待测图像块进行识别.在不重叠分块情况下先大致判断篡改区域,然后在该区域内逐像素分块判别,最终实现篡改区域精确定位.实验结果表明,对128 dpi×128 dpi图像块的识别率达到94.75％,高于现有方法;对合成图像篡改区域能够实现精确定位,且对旋转、缩放操作表现出较好的顽健性.     

一种基于非线性扩散方程和Hausdorff测度理论的SAR图像与光学图像配准方法

该文提出了一种新的利用非线性扩散方程与Hausdorff测度的合成孔径雷达(SAR)图像与可见光图像的配准算法。在此算法中,首先利用非线性扩散方程的SAR图像分割算法获得SAR图像与光学二值图像中相对应的闭合区域特征,将闭合区域质心坐标重合后,被提取特征可通过Hausdorff测度与遗传算法对图像进行快速粗匹配。在粗配准的基础上最后使用二值图像的相关度来进行精配准。实验结果表明,本文方法鲁棒性好,配准精度高,能自动完成存在较大坐标平移、角度变换、尺度缩放的待配图像的配准。     

Rotation, scale, and translation resilient watermarking for images

Many electronic watermarks for still images and video content are sensitive to geometric distortions. For example, simple rotation, scaling, and/or translation (RST) of an image can prevent blind detection of a public watermark. In this paper, we propose a watermarking algorithm that is robust to RST distortions. The watermark is embedded into a one-dimensional (1-D) signal obtained by taking the Fourier transform of the image, resampling the Fourier magnitudes into log-polar coordinates, and then summing a function of those magnitudes along the log-radius axis. Rotation of the image results in a cyclical shift of the extracted signal. Scaling of the image results in amplification of the extracted signal, and translation of the image has no effect on the extracted signal. We can therefore compensate for rotation with a simple search, and compensate for scaling by using the correlation coefficient as the detection measure. False positive results on a database of 10 000 images are reported. Robustness results on a database of 2000 images are described. It is shown that the watermark is robust to rotation, scale, and translation. In addition, we describe tests examining the watermarks resistance to cropping and JPEG compression.     

SIFT-Symmetry: A robust detection method for copy-move forgery with reflection attack

Copy-move forgery (CMF) is a popular image manipulation technique that is simple and effective in creating forged illustrations. The bulk of CMF detection methods concentrate on common geometrical transformation attacks (e.g., rotation and scale) and post-processing attacks (e.g., Joint Photographic Experts Group (JPEG) compression and Gaussian noise addition). However, geometrical transformation that involves reflection attacks has not yet been highlighted in the literature. As the threats of reflection attack are inevitable, there is an urgent need to study CMF detection methods that are robust against this type of attack. In this study, we investigated common geometrical transformation attacks and reflection-based attacks. Also, we suggested a robust CMF detection method, called SIFT-Symmetry, that innovatively combines the Scale Invariant Feature Transform (SIFT)-based CMF detection method with symmetry-based matching. We evaluated the SIFT-Symmetry with three established methods that are based on SIFT, multi-scale analysis, and patch matching using two new datasets that cover simple transformation and reflection-based attacks. The results show that the F-score of the SIFT-Symmetry method surpassed the average 80% value for all geometrical transformation cases, including simple transformation and reflection-based attacks, except for the reflection with rotation case which had an average F-score of 65.3%. The results therefore show that the SIFT-Symmetry method gives better performance compared to the other existing methods.     

使用M进制小波对尺度与旋转不变的图像特征点进行检测

基于小波变换和尺度空间理论,提出了一种尺度与旋转不变的图像特征点的检测方法。首先对图像进行多尺度的M进制小波变换,然后根据M进制小波变换系数的能量构造对应的二阶矩阵,最后通过考察该矩阵的特征值确定图像的特征点。实验表明,与目前最常用的方法相比,本文方法对图像的旋转变化与尺度变化均具有更好的不变性,在光照变化和噪声干扰等外部条件影响下也能保持较高的鲁棒性。     

稳健性图像复制-黏贴篡改被动认证

图像复制-黏贴(copy-move)是一类的常见的图像篡改手段,篡改通过将图像中一部分区域复制并黏贴到同一幅图像另一区域后起到掩盖被覆盖内容的目的。由于篡改者为了使篡改更加逼真或者试图增加检测难度,往往在黏贴图像块之前对图像块进行加噪、模糊或者旋转缩放等后续处理。目前检测这类篡改的认证方法主要归纳为三类：变换域鲁棒特征子块匹配方法、旋转不变特征子块匹配方法和特征点匹配方法。本文对采用这三类方法的国内外文献进行了系统的分析和归纳并对未来研究方向进行了展望。     

Monochromatic-Based Method for Impulse Noise Detection and Suppression in Color Images

A new method to detect and reduce the impulse noise in color images is presented in this paper. The method consists of two stages: detection and filtering. Since each of the individual channels (components) of the color image can be considered as a monochrome image, both stages are applied to each channel separately, and then the individual results are combined into one output image. The corrupted pixels are detected in the first stage based on a proposed innovative switching technique. The noise-free pixels are copied to their corresponding locations in the output image. In the second stage, average filtering is applied only to those pixels which are determined to be noisy in the first stage, and only noise-free pixel values are involved in calculating this average. The size of the sliding window depends on the estimated noise density and is very small even for high noise densities. The proposed method is effective in noise reduction while preserving edge details and color chromaticity. Simulation results show that the proposed method outperforms all the tested existing state-of-the-art methods used in digital color image restoration in both standard objective measurements and perceived image quality.     

一种不变的基于傅立叶变换的区域形状描述子

 提出了一种不变的基于傅立叶变换的区域形状描述子.该方法首先将区域形状图像用极坐标光栅重新采样成形状像素矩阵,然后对该矩阵进行两次一维傅立叶变换和一次相位修正操作,最后用低频傅立叶系数构成的矩阵作为形状描述子.该形状描述子不仅保留了傅立叶系数中的相位信息,而且满足不变性.实验结果表明该方法要优于现有的傅立叶区域形状描述方法和Zernike矩形状描述方法.     

Rotation, scaling and translation invariant image watermarking using feature points

In this article, a novel robust image watermarking scheme is presented to resist rotation, scaling, and translation （RST）. Initially, the original image is scale normalized, and the feature points are then extracted. Furthermore, the locally most stable feature points are used to generate several nonoverlapped circular regions. These regions are then rotation normalized to generate the invariant regions. Watermark embedding and extraction are implemented in the invariant regions in discrete cosine transform domain. In the decoder, the watermark can be extracted without the original image. Simulation results show that the proposed scheme is robust to traditional signal processing attacks, RST attacks, as well as some combined attacks.     

基于图像检测识别的数据增强技术

当前,在图像目标检测识别方面,深度学习技术已经成为研究的热点。然而深度学习在进行网络训练时需要使用大量的样本,当样本数目较少时,得到的训练模型其检测效果往往不佳。介绍了色彩变换、水平翻转、旋转、亮度变换、缩放、裁剪、添加噪声等不同数据增强方法,并结合VOC2007数据集,采用数据增强技术实现样本扩充。实验结果表明对样本进行数据增强处理,均可以在一定程度上提高图像检测精度。特别是色彩变换、水平翻转、旋转、亮度变换和缩放这五种方法扩展训练集,对最终检测效果提升较为明显。     

结合手势二进制编码和类-Hausdorff距离的手势识别

针对目前动态手势识别方法受手势旋转、平移、缩放的影响,并解决手势识别的实时性问题,提出一种基于手势二进制编码和类-Hausdorff距离模板匹配的手势识别方法.首先,把分割好的手势图像进行标准化处理,求出标准化图像中的手势主方向,建立二维手势直角坐标系,提取空间手势特征;其次,根据前五帧手势图像中手势像素点个数的变化量识别出动态手势类型;然后,用手势二进制描述子从动态手势类型中再筛选出可能的候选手势集合;最后,用类-Hausdorff距离模板匹配方法从候选手势集合中识别出最终手势.主要创新点在于：提出的动态手势类型识别和手势二进制描述子匹配的方法,大大缩短了动态手势识别的时间;提出的结合手势主方向的类-Hausdorff距离方法,不仅对旋转、平移和缩放手势具有不变性,而且对区分度较小的手势也具有较高的识别准确率.实验结果表明,在光照相对稳定的条件下,该方法能够实时准确的实现动态手势识别,总体识别率达到95%以上,对发生缩放的手势识别率能达到92%以上,对发生旋转的手势识别率能达到87%以上.本文算法已经在一个基于手势的人机交互界面中得到应用.     

基于场景复杂度与不变特征的航拍视频实时配准算法

实时、鲁棒的图像配准是航拍视频电子稳像、全景图拼接和地面运动目标自动检测与跟踪的前提和关键技术.本文以航拍视频序列为处理对象,提出了一种新的基于场景复杂度与不变特征的实时配准算法,其主要特点包括：(1)在对航拍视频配准难点进行详细分析的基础上,有针对性的提出基于积分图的快速图像尺度空间构建、依据场景复杂度的检测特征点数量在线精确控制、基于描述子误差分布统计特性级的联分类器构造等新方法,使得算法配准性能不随场景的复杂度发生改变,能够在各种地貌条件下实时、稳定的进行图像配准;(2)将多尺度Harris角点和SIFT描述子相结合,并通过对帧间变换模型参数进行鲁棒估计,保证了算法具有良好的旋转、尺度、亮度不变性和配准精度.实验结果表明,算法可在场景变化、图像大幅度平移、尺度缩放和任意角度旋转等复杂条件下实时、精确的进行图像配准,对分辨率为320×240的航拍序列的平均处理速度达到20.7帧/秒.