A New Forgery Image Dataset and its Subjective Evaluation

Faria Hossain; Tasos Dagiuklas; Athanassios Skodras

doi:10.1109/GlobConET56651.2023.10150020

A New Forgery Image Dataset and its Subjective Evaluation

Faria Hossain, Tasos Dagiuklas, Athanassios Skodras

University of Patras

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

4 Downloads (Pure)

Abstract

The aim of this research paper is to present a new forgery image dataset with a thorough subjective evaluation in detecting manipulated images, considering various parameters. The original images were obtained from public sources, and meaningful forgeries were produced using an image editing plat- form with three techniques: cut-paste, copy-move, and erase-fill. Both pre-processing and post-processing methods were used to generate fake images. The subjective evaluation revealed that the accuracy of manipulated image detection was affected by various factors, such as user type, image quantity, tampering method, and image resolution, which were analyzed using quantitative data.

Original language	English
Title of host publication	2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350331790
DOIs	https://doi.org/10.1109/GlobConET56651.2023.10150020 https://doi.org/10.1109/globconet56651.2023.10150020
Publication status	Published - 19 May 2023
Event	2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023 - London, United Kingdom Duration: 19 May 2023 → 21 May 2023

Publication series

Name	2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

Conference

Conference	2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023
Country/Territory	United Kingdom
City	London
Period	19/05/23 → 21/05/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Forgery Image Dataset
Image Manipulation
Subjective Assessment
Tampering Detection

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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A New Forgery Image Dataset and its Subjective EvaluationAccepted author manuscript, 2.04 MBLicence: CC BY 4.0
A New Forgery Image Dataset and its Subjective Evaluation

Cite this

Hossain, F., Dagiuklas, T., & Skodras, A. (2023). A New Forgery Image Dataset and its Subjective Evaluation. In 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023 (2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobConET56651.2023.10150020, https://doi.org/10.1109/globconet56651.2023.10150020

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title = "A New Forgery Image Dataset and its Subjective Evaluation",

abstract = "The aim of this research paper is to present a new forgery image dataset with a thorough subjective evaluation in detecting manipulated images, considering various parameters. The original images were obtained from public sources, and meaningful forgeries were produced using an image editing plat- form with three techniques: cut-paste, copy-move, and erase-fill. Both pre-processing and post-processing methods were used to generate fake images. The subjective evaluation revealed that the accuracy of manipulated image detection was affected by various factors, such as user type, image quantity, tampering method, and image resolution, which were analyzed using quantitative data.",

keywords = "Forgery Image Dataset, Image Manipulation, Subjective Assessment, Tampering Detection",

author = "Faria Hossain and Tasos Dagiuklas and Athanassios Skodras",

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year = "2023",

month = may,

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language = "English",

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Hossain, F , Dagiuklas, T & Skodras, A 2023, A New Forgery Image Dataset and its Subjective Evaluation. in 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023. 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023, Institute of Electrical and Electronics Engineers Inc., 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023, London, United Kingdom, 19/05/23. https://doi.org/10.1109/GlobConET56651.2023.10150020, https://doi.org/10.1109/globconet56651.2023.10150020

A New Forgery Image Dataset and its Subjective Evaluation. / Hossain, Faria ; Dagiuklas, Tasos; Skodras, Athanassios.
2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A New Forgery Image Dataset and its Subjective Evaluation

AU - Hossain, Faria

AU - Dagiuklas, Tasos

AU - Skodras, Athanassios

PY - 2023/5/19

Y1 - 2023/5/19

N2 - The aim of this research paper is to present a new forgery image dataset with a thorough subjective evaluation in detecting manipulated images, considering various parameters. The original images were obtained from public sources, and meaningful forgeries were produced using an image editing plat- form with three techniques: cut-paste, copy-move, and erase-fill. Both pre-processing and post-processing methods were used to generate fake images. The subjective evaluation revealed that the accuracy of manipulated image detection was affected by various factors, such as user type, image quantity, tampering method, and image resolution, which were analyzed using quantitative data.

AB - The aim of this research paper is to present a new forgery image dataset with a thorough subjective evaluation in detecting manipulated images, considering various parameters. The original images were obtained from public sources, and meaningful forgeries were produced using an image editing plat- form with three techniques: cut-paste, copy-move, and erase-fill. Both pre-processing and post-processing methods were used to generate fake images. The subjective evaluation revealed that the accuracy of manipulated image detection was affected by various factors, such as user type, image quantity, tampering method, and image resolution, which were analyzed using quantitative data.

KW - Forgery Image Dataset

KW - Image Manipulation

KW - Subjective Assessment

KW - Tampering Detection

UR - https://www.scopus.com/pages/publications/85164273452

U2 - 10.1109/GlobConET56651.2023.10150020

DO - 10.1109/GlobConET56651.2023.10150020

M3 - Conference contribution

T3 - 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

BT - 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023

Y2 - 19 May 2023 through 21 May 2023

ER -

Hossain F , Dagiuklas T, Skodras A. A New Forgery Image Dataset and its Subjective Evaluation. In 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023). doi: 10.1109/GlobConET56651.2023.10150020, 10.1109/globconet56651.2023.10150020

A New Forgery Image Dataset and its Subjective Evaluation

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

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