research-article

Blur Invariant Block based Copy-Move Forgery Detection Technique using FWHT Features

Authors:

Dalton Meitei ThounaojamAuthors Info & Claims

ICWIP 2017: Proceedings of the International Conference on Watermarking and Image Processing

Pages 22 - 26

https://doi.org/10.1145/3150978.3150987

Published: 06 September 2017 Publication History

Abstract

Copy-move forgery detection has become a prominent research area. In this paper, an efficient block based copy-move forgery detection algorithm based on Fast Walsh Hadamard Transform is presented with an objective to reduce processing time in identifying the duplicated regions in an image. Forged regions are detected using lexicographical sorting and efficient shift vector mechanism. Proposed system is tested on different attacked images of the CoMoFoD dataset. Attacks are blur movement, brightness changes, color reduction and contrast adjustment, etc. Performance of proposed system is quite good across all the attacks. Also, it is more robust to blur movement. Experimental results show the ability of the proposed method to accurately detect the tampered regions as well as reducing the time complexity.

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Cited By

Alencar ALopes MFernandes AAnjos JDe Paz Santana JLeithardt V(2024)Detection of Forged Images Using a Combination of Passive Methods Based on Neural NetworksFuture Internet10.3390/fi1603009716:3(97)Online publication date: 14-Mar-2024
https://doi.org/10.3390/fi16030097
Capasso PCattaneo GDe Marsico M(2024)A Comprehensive Survey on Methods for Image IntegrityACM Transactions on Multimedia Computing, Communications, and Applications10.1145/363320320:11(1-34)Online publication date: 12-Sep-2024
https://dl.acm.org/doi/10.1145/3633203
Kumar DPandey RMishra A(2024)A review of image features extraction techniques and their applications in image forensicMultimedia Tools and Applications10.1007/s11042-023-17950-x83:40(87801-87902)Online publication date: 20-Mar-2024
https://doi.org/10.1007/s11042-023-17950-x
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Blur Invariant Block based Copy-Move Forgery Detection Technique using FWHT Features
1. Computing methodologies
  1. Computer graphics

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ICWIP 2017: Proceedings of the International Conference on Watermarking and Image Processing

September 2017

70 pages

ISBN:9781450353076

DOI:10.1145/3150978

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 06 September 2017

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ICWIP 2017

ICWIP 2017: International Conference on Watermarking and Image Processing

September 6 - 8, 2017

Paris, France

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Cited By

Alencar ALopes MFernandes AAnjos JDe Paz Santana JLeithardt V(2024)Detection of Forged Images Using a Combination of Passive Methods Based on Neural NetworksFuture Internet10.3390/fi1603009716:3(97)Online publication date: 14-Mar-2024
https://doi.org/10.3390/fi16030097
Capasso PCattaneo GDe Marsico M(2024)A Comprehensive Survey on Methods for Image IntegrityACM Transactions on Multimedia Computing, Communications, and Applications10.1145/363320320:11(1-34)Online publication date: 12-Sep-2024
https://dl.acm.org/doi/10.1145/3633203
Kumar DPandey RMishra A(2024)A review of image features extraction techniques and their applications in image forensicMultimedia Tools and Applications10.1007/s11042-023-17950-x83:40(87801-87902)Online publication date: 20-Mar-2024
https://doi.org/10.1007/s11042-023-17950-x
Soni BDas PSoni BDas P(2022)Background Study and AnalysisImage Copy-Move Forgery Detection10.1007/978-981-16-9041-9_2(11-31)Online publication date: 4-Feb-2022
https://doi.org/10.1007/978-981-16-9041-9_2
Mathur PSoni B(2021)Exploring Color Models for Enhancement of Underwater ImageData Driven Approach Towards Disruptive Technologies10.1007/978-981-15-9873-9_26(325-336)Online publication date: 7-Apr-2021
https://doi.org/10.1007/978-981-15-9873-9_26
Dixit ABag S(2020)Utilization of edge operators for localization of copy-move image forgery using WLD-HOG features with connected component labelingMultimedia Tools and Applications10.1007/s11042-020-09230-9Online publication date: 10-Jul-2020
https://doi.org/10.1007/s11042-020-09230-9
Kharanghar MDoegar A(2020)Copy-Move Forgery Detection Methods: A CritiqueAdvances in Information Communication Technology and Computing10.1007/978-981-15-5421-6_49(501-523)Online publication date: 19-Aug-2020
https://doi.org/10.1007/978-981-15-5421-6_49
Soni BDas PThounaojam D(2019)Geometric transformation invariant block based copy-move forgery detection using fast and efficient hybrid local featuresJournal of Information Security and Applications10.1016/j.jisa.2019.01.00745:C(44-51)Online publication date: 1-Apr-2019
https://dl.acm.org/doi/10.1016/j.jisa.2019.01.007
Soni BDas PThounaojam DBiswas D(2019)Copy–Move Attack Detection from Digital Images: An Image Forensic ApproachSmart Computing Paradigms: New Progresses and Challenges10.1007/978-981-13-9683-0_8(69-76)Online publication date: 1-Dec-2019
https://doi.org/10.1007/978-981-13-9683-0_8
Soni BDas PThounaojam D(2018)multiCMFDProceedings of the 2018 International Conference on Image and Graphics Processing10.1145/3191442.3191465(53-58)Online publication date: 24-Feb-2018
https://dl.acm.org/doi/10.1145/3191442.3191465
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