Image authentication by statistical analysis

Author

Tong Qiao ; Retraint, Florent ; COGRANNE, Remi

Author_Institution

LM2S, Univ. de Technol. de Troyes (UTT), Troyes, France

fYear

2013

fDate

9-13 Sept. 2013

Firstpage

1

Lastpage

5

Abstract

This paper investigates the discrimination between Photographic Images (PIM) and Computer Generated (CG) images. The proposed method exploits traces of Color Filter Array (CFA) interpolation, present in PIM images, together with the use of hypothesis testing theory. By using the Likelihood Ratio Test (LRT), the method proposed to distinguish PIM from CG images warrants a prescribed False Alarm Rate (FAR) and achieves the maximal detection power. Experimental results show the efficiency of the proposed methodology and the high robustness with respect to anti-forensic techniques.

Keywords

image forensics; interpolation; statistical analysis; CFA interpolation; PIM images; anti-forensic techniques; color filter array; computer generated images; false alarm rate; hypothesis testing theory; image authentication; likelihood ratio test; photographic images; statistical analysis; Forensics; Image color analysis; Noise; Parametric statistics; Robustness; Testing; Vectors; CG; PIM; hypothesis testing; image forensics; linear parametric model; nuisance parameters;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Conference (EUSIPCO), 2013 Proceedings of the 21st European

Conference_Location

Marrakech

Type

conf

Filename

6811485