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A generalization of Benford's law and its application to images
Abstract and Figures
We present a generalization of Benford's law for the first sig-nificant digit. This generalization is based on keeping two terms of the Fourier expansion of the probability density func-tion of the data in the modular logarithmic domain. We prove that images in the Discrete Cosine Transform domain closely follow this generalization. We use this property to propose an application in image forensics, namely, detecting that a given image carries a hidden message.
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