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Medical image integrity control and forensics based on watermarking — Approximating local modifications and identifying global image alterations

机译:基于水印的医学图像完整性控制和取证—近似局部修改并识别全局图像更改

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In this paper we present a medical image integrity verification system that not only allows detecting and approximating malevolent local image alterations (e.g. removal or addition of findings) but is also capable to identify the nature of global image processing applied to the image (e.g. lossy compression, filtering …). For that purpose, we propose an image signature derived from the geometric moments of pixel blocks. Such a signature is computed over regions of interest of the image and then watermarked in regions of non interest. Image integrity analysis is conducted by comparing embedded and recomputed signatures. If any, local modifications are approximated through the determination of the parameters of the nearest generalized 2D Gaussian. Image moments are taken as image features and serve as inputs to one classifier we learned to discriminate the type of global image processing. Experimental results with both local and global modifications illustrate the overall performances of our approach.
机译:在本文中,我们提出了一种医学图像完整性验证系统,该系统不仅可以检测和近似恶意的局部图像变化(例如,移除或增加发现),而且还可以识别应用于图像的全局图像处理的性质(例如,有损压缩) ,过滤...)。为此,我们提出了一种从像素块的几何矩导出的图像签名。在图像的感兴趣区域上计算这样的签名,然后在不感兴趣的区域中加水印。通过比较嵌入和重新计算的签名来进行图像完整性分析。如果有的话,可以通过确定最接近的广义2D高斯参数来近似进行局部修改。图像矩被当作图像特征,并作为我们学习来区分全局图像处理类型的一个分类器的输入。局部和全局修改的实验结果说明了我们方法的整体性能。

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