A Watermarking-Based Medical Image Integrity Control System and an Image Moment Signature for Tampering Characterization
A Watermarking-Based Medical Image Integrity Control System and an Image Moment Signature for Tampering Characterization
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DOI：
10.1109/jbhi.2013.2263533
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发表时间：
2013-11-01
影响因子：
7.7
通讯作者：
Roux, Christian
中科院分区：
文献类型：
--
作者：
Coatrieux, Gouenou;Huang, Hui;Roux, Christian
在本文中，我们提出了一个医学图像完整性验证系统来检测和逼近局部恶意图像更改（例如，例如，在一个实施例中，去除或增加损伤）以及识别图像可能已经经历的全局处理的性质（例如，例如，在一个实施例中，有损压缩、滤波等）。建议的完整性分析过程是基于非重要区域水印的签名提取从不同的感兴趣的像素块，这是在验证阶段的重新计算的比较。提出了一组三个签名。前两个专门用于检测和修改位置的密码散列和校验和，而最后一个是从图像矩理论发出。在本文中，我们首先展示了如何几何矩可以用来近似任何局部修改其最近的广义二维高斯。然后，我们演示了如何原始和重新计算的几何矩之间的比率可以被用作图像特征，在一个基于分类器的策略，以确定一个全局图像处理的性质。考虑局部和全局修改MRI和视网膜图像的实验结果说明了我们的方法的整体性能。利用大约200位长的像素块签名，可以检测、粗略定位和了解图像篡改。
In this paper, we present a medical image integrity verification system to detect and approximate local malevolent image alterations (e. g., removal or addition of lesions) as well as identifying the nature of a global processing an image may have undergone (e. g., lossy compression, filtering, etc.). The proposed integrity analysis process is based on nonsignificant region watermarking with signatures extracted from different pixel blocks of interest, which are compared with the recomputed ones at the verification stage. A set of three signatures is proposed. The first two devoted to detection and modification location are cryptographic hashes and checksums, while the last one is issued from the image moment theory. In this paper, we first show how geometric moments can be used to approximate any local modification by its nearest generalized 2-D Gaussian. We then demonstrate how ratios between original and recomputed geometric moments can be used as image features in a classifier-based strategy in order to determine the nature of a global image processing. Experimental results considering both local and global modifications in MRI and retina images illustrate the overall performances of our approach. With a pixel block signature of about 200 bit long, it is possible to detect, to roughly localize, and to get an idea about the image tamper.