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Medical Image Blind Integrity Verification with Krawtchouk Moments

机译:医学图像盲人完整性验证与krawtchouk矩

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摘要

A new blind integrity verification method for medical image is proposed in this paper. It is based on a new kind of image features, known as Krawtchouk moments, which we use to distinguish the original images from the modified ones. Basically, with our scheme, image integrity verification is accomplished by classifying images into the original and modified categories. Experiments conducted on medical images issued from different modalities verified the validity of the proposed method and demonstrated that it can be used to detect and discriminate image modifications of different types with high accuracy. We also compared the performance of our scheme with a state-of-the-art solution suggested for medical images—solution that is based on histogram statistical properties of reorganized block-based Tchebichef moments. Conducted tests proved the better behavior of our image feature set.
机译:本文提出了一种新的盲人完整性验证方法。 它基于一种新的图像特征,称为krawtchouk的瞬间,我们用于区分原始图像从修改后的图像。 基本上,通过我们的方案,通过将图像分类为原始和修改的类别来完成图像完整性验证。 在不同方式发布的医学图像上进行的实验验证了所提出的方法的有效性,并证明它可用于以高精度检测和区分不同类型的图像修改。 我们还将我们的方案的性能与用于医学图像的最先进的解决方案进行了比较,这是基于重组基于块的Tchebichef矩的直方图统计特性的医学图像解决方案。 进行的测试证明了我们的图像功能集的更好行为。

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