Institute of Information Theory and Automation

Publication details

Using noise inconsistencies for blind image forensics

Journal Article

Saic Stanislav, Mahdian Babak


serial: Image and Vision Computing vol.27, 10 (2009), p. 1497-1503

research: CEZ:AV0Z10750506

project(s): GA102/08/0470, GA ČR

keywords: Image forensics, Digital forgery, Image tampering, Image segmentation

preview: Download

abstract (eng):

A commonly used tool to conceal the traces of tampering is the addition of locally random noise to the altered image regions. The noise degradation is the main cause of failure of many active or passive image forgery detection methods. The amount of noise is uniform across the entire authentic image. Adding locally random noise may cause inconsistencies in the image’s noise. Therefore, the detection of various noise levels in an image may signify tampering. In this paper, we propose a novel method capable of dividing an investigated image into various partitions with homogenous noise levels. In other words, we introduce a segmentation method detecting changes in noise level. We assume the additive white Gaussian noise. Several examples are shown to demonstrate the proposed method’s output. An extensive quantitative measure of the efficiency of the noise estimation part as a function of different noise standard deviations, region sizes and various JPEG compression qualities is proposed as well.

abstract (cze):

Obvyklý způsob, kterým se zakrývá úprava fotografií je přidání aditivního šumu. Přítomnost šumu znesnadňuje detekci těchto úprav.Avšak přidání lokálního šumu může způsobit nespojitosti šumu obrazu. V článku je navržena nová metoda, která je umožňuje rozdělení obrazu na části s homogením šumem. Na řadě experimentů je demonstrována účinnost metody a její závislost na JPEG komprimaci.

RIV: IN

Responsible for information: admin
Last modification: 21.12.2012
Institute of Information Theory and Automation