从光度法修改的虹膜图像计算图像系统发育树

Sudipta Banerjee, A. Ross
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引用次数: 2

摘要

虹膜识别需要使用虹膜图像来识别个体。在某些情况下,从个体获得的虹膜图像可以通过对其进行连续的光度变换(如增亮、伽马校正、中值滤波和高斯平滑)来进行修改,从而产生一系列变换后的图像。在数字图像取证的背景下,自动推断变换图像之间的关系是很重要的。在这方面,我们开发了一种从一组这样的转换图像生成图像系统发育树(IPT)的方法。我们的策略需要将任意光度变换建模为线性或非线性函数,并利用模型的参数来量化图像对之间的关系。然后使用估计的参数来生成IPT。在参数估计和IPT生成方面获得了适度但有希望的结果。
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Computing an image Phylogeny Tree from photometrically modified iris images
Iris recognition entails the use of iris images to recognize an individual. In some cases, the iris image acquired from an individual can be modified by subjecting it to successive photometric transformations such as brightening, gamma correction, median filtering and Gaussian smoothing, resulting in a family of transformed images. Automatically inferring the relationship between the set of transformed images is important in the context of digital image forensics. In this regard, we develop a method to generate an Image Phylogeny Tree (IPT) from a set of such transformed images. Our strategy entails modeling an arbitrary photometric transformation as a linear or non-linear function and utilizing the parameters of the model to quantify the relationship between pairs of images. The estimated parameters are then used to generate the IPT. Modest, yet promising, results are obtained in terms of parameter estimation and IPT generation.
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