Noisesniffer: A Fully Automatic Image Forgery Detector Based on Noise Analysis

Marina Gardella; Pablo Muse; Jean-Michel Morel; Miguel Colom

doi:10.1109/IWBF50991.2021.9465095

Noisesniffer: A Fully Automatic Image Forgery Detector Based on Noise Analysis

Marina Gardella
, Pablo Muse
, Jean-Michel Morel
, Miguel Colom

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

20 Citations (Scopus)

Abstract

Images undergo a complex processing chain from the moment light reaches the camera's sensor until the final digital image is delivered. Each of these operations leave traces on the noise model which enable forgery detection through noise analysis. In this article we define a background stochastic model which makes it possible to detect local noise anomalies characterized by their number of false alarms. The proposed method is both automatic and blind, allowing quantitative and subjectivity-free detections. Results show that the proposed method outperforms the state of the art. © 2021 IEEE.

Original language	English
Title of host publication	Proceedings - 2021 International Workshop on Biometrics and Forensics (IWBF 2021)
Publisher	IEEE
ISBN (Electronic)	9781728195568
ISBN (Print)	9781728195575
DOIs	https://doi.org/10.1109/IWBF50991.2021.9465095
Publication status	Published - 2021
Externally published	Yes
Event	9th IEEE International Workshop on Biometrics and Forensics (IWBF 2021) - Roma Tre University (Virtual), Rome, Italy Duration: 6 May 2021 → 7 May 2021 https://iwbf2021.com/

Publication series

Name	Proceedings - International Workshop on Biometrics and Forensics, IWBF

Conference

Conference	9th IEEE International Workshop on Biometrics and Forensics (IWBF 2021)
Place	Italy
City	Rome
Period	6/05/21 → 7/05/21
Internet address	https://iwbf2021.com/

Funding

This work was supported by a grant from Région Île-de-France.

Research Keywords

automatic forgery detection
blind algorithm
image forensics
noise residual

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10.1109/IWBF50991.2021.9465095

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@inproceedings{207c0c0231d44a0581fba545ad1c43f8,

title = "Noisesniffer: A Fully Automatic Image Forgery Detector Based on Noise Analysis",

abstract = "Images undergo a complex processing chain from the moment light reaches the camera's sensor until the final digital image is delivered. Each of these operations leave traces on the noise model which enable forgery detection through noise analysis. In this article we define a background stochastic model which makes it possible to detect local noise anomalies characterized by their number of false alarms. The proposed method is both automatic and blind, allowing quantitative and subjectivity-free detections. Results show that the proposed method outperforms the state of the art. {\textcopyright} 2021 IEEE.",

keywords = "automatic forgery detection, blind algorithm, image forensics, noise residual",

author = "Marina Gardella and Pablo Muse and Jean-Michel Morel and Miguel Colom",

year = "2021",

doi = "10.1109/IWBF50991.2021.9465095",

language = "English",

isbn = "9781728195575",

series = "Proceedings - International Workshop on Biometrics and Forensics, IWBF",

publisher = "IEEE",

booktitle = "Proceedings - 2021 International Workshop on Biometrics and Forensics (IWBF 2021)",

address = "United States",

note = "9th IEEE International Workshop on Biometrics and Forensics (IWBF 2021) ; Conference date: 06-05-2021 Through 07-05-2021",

url = "https://iwbf2021.com/",

}

Gardella, M, Muse, P, Morel, J-M & Colom, M 2021, Noisesniffer: A Fully Automatic Image Forgery Detector Based on Noise Analysis. in Proceedings - 2021 International Workshop on Biometrics and Forensics (IWBF 2021)., 9465095, Proceedings - International Workshop on Biometrics and Forensics, IWBF, IEEE, 9th IEEE International Workshop on Biometrics and Forensics (IWBF 2021), Rome, Italy, 6/05/21. https://doi.org/10.1109/IWBF50991.2021.9465095

Noisesniffer: A Fully Automatic Image Forgery Detector Based on Noise Analysis. / Gardella, Marina; Muse, Pablo; Morel, Jean-Michel et al.
Proceedings - 2021 International Workshop on Biometrics and Forensics (IWBF 2021). IEEE, 2021. 9465095 (Proceedings - International Workshop on Biometrics and Forensics, IWBF).

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

TY - GEN

T1 - Noisesniffer

T2 - 9th IEEE International Workshop on Biometrics and Forensics (IWBF 2021)

AU - Gardella, Marina

AU - Muse, Pablo

AU - Morel, Jean-Michel

AU - Colom, Miguel

PY - 2021

Y1 - 2021

N2 - Images undergo a complex processing chain from the moment light reaches the camera's sensor until the final digital image is delivered. Each of these operations leave traces on the noise model which enable forgery detection through noise analysis. In this article we define a background stochastic model which makes it possible to detect local noise anomalies characterized by their number of false alarms. The proposed method is both automatic and blind, allowing quantitative and subjectivity-free detections. Results show that the proposed method outperforms the state of the art. © 2021 IEEE.

AB - Images undergo a complex processing chain from the moment light reaches the camera's sensor until the final digital image is delivered. Each of these operations leave traces on the noise model which enable forgery detection through noise analysis. In this article we define a background stochastic model which makes it possible to detect local noise anomalies characterized by their number of false alarms. The proposed method is both automatic and blind, allowing quantitative and subjectivity-free detections. Results show that the proposed method outperforms the state of the art. © 2021 IEEE.

KW - automatic forgery detection

KW - blind algorithm

KW - image forensics

KW - noise residual

UR - https://www.scopus.com/pages/publications/85113890060

UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85113890060&origin=recordpage

U2 - 10.1109/IWBF50991.2021.9465095

DO - 10.1109/IWBF50991.2021.9465095

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781728195575

T3 - Proceedings - International Workshop on Biometrics and Forensics, IWBF

BT - Proceedings - 2021 International Workshop on Biometrics and Forensics (IWBF 2021)

PB - IEEE

Y2 - 6 May 2021 through 7 May 2021

ER -

Noisesniffer: A Fully Automatic Image Forgery Detector Based on Noise Analysis

Abstract

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Research Keywords

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