Blind Forensics Tool Of Falsification For RAW Images

被引：0

作者：

Thi Ngoc Canh Doan ^{[1
]}

Retraint, Florent ^{[1
]}

Zitzmann, Cathel ^{[2
]}

机构：

[1] Univ Technol Troyes, ICD, LM2S, Troyes, France

[2] EPF Grad Sch Engn, ICD, LM2S, Montpellier, France

来源：

2017 IEEE INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND INFORMATION TECHNOLOGY (ISSPIT) | 2017年

关键词：

Digital forensics; blind image forgery detection; hypothesis testing; image models;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a novel method for blind forgery detection of natural image in RAW format. The approach is based on a statistical noise model of natural RAW images. This model is characterized by two parameters which are used as a fingerprint to falsification identification. The identification is cast in the framework of the hypothesis testing theory. For practice use, the Generalized Likelihood Ratio Test (GLRT) is presented and its performance is theoretically established in case of unknown parameters where an estimation of those parameters is designed. Experiments with simulated and real images highlight the relevance of the proposed approach.

引用

页码：18 / 23

页数：6

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