An efficient expanding block algorithm for image copy-move forgery detection

Lynch, Gavin; Shih, Frank Y.; Liao, Hong-Yuan Mark

doi:10.1016/j.ins.2013.03.028

Cited by 106 publications

(49 citation statements)

References 16 publications

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“…Table I presents the performance of PCM algorithm compared to four other algorithms; DCT [1], EB [4], PCA [5] and CRMS [6] algorithms.…”

Section: Comparison With Other Methodsmentioning

confidence: 99%

“…In this experiment, the average execution time for 1000 forged images used in this research. Table I presents the time performance of PCM algorithm compared to DCT [1], EB [4], PCA [5] and CRMS [6] algorithms. It is noticed that PCM takes the highest execution time while CRMS has the lowest.…”

Section: Comparison With Other Methodsmentioning

confidence: 99%

“…Lynch et al [4] utilize the average intensity of each block as the RF. The authors propose an Expanding Blocking (EB) scheme to speed up the matching process, as well as to evaluate their system accuracy under JPEG compression and blurring effects.…”

Section: Related Workmentioning

confidence: 99%

“…Fig5c presents the sorting procedure (directions are declared as arrows). For example, 3 f moved to the 1st column, 2 f moved to the 2nd column, 4 f moved to the 3rd column and 1 f became the 4th column. Here we describe radix sort in lexicographical order in detail.…”

Section: B Fourier Transformmentioning

confidence: 99%

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Copy Move Image Forgery Detection Based on Polar Fourier Representation

Wang¹,

Kamata

2018

IJMLC

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Abstract-With the rapid development of multimedia technology, it's easy for someone to obtain an image and edit it according to their own preferences or some ulterior purpose. Copy-Move is a common type of digital image forgery where a part of the original image is copied and pasted at another position in the same image. In this paper, we propose an efficient methodology for enhancing block matching based on Copy-Move forgery detection. The main contribution of this work is the utilization of polar representation to get the representative features for each block. The main feature used in this paper is the frequency of each block based on Fourier transform. The experimental results show the efficiency of the proposed method for detecting copy-move regions, even when the copied region has undergone severe image manipulations such as rotation, scaling, Gaussian blurring, brightness modification, JPEG compression and noise addition.

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“…Table I presents the performance of PCM algorithm compared to four other algorithms; DCT [1], EB [4], PCA [5] and CRMS [6] algorithms.…”

Section: Comparison With Other Methodsmentioning

confidence: 99%

Section: Comparison With Other Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: B Fourier Transformmentioning

confidence: 99%

See 2 more Smart Citations

Copy Move Image Forgery Detection Based on Polar Fourier Representation

Wang¹,

Kamata

2018

IJMLC

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“…DyWT is scale invariant and hence it is robust to attack like scaling. Many other researchers have also worked on copy move forgery detection techniques to improve the computational efficiency, flexibility and robustness of the algorithm including Akbarpour et al [18], Lynch et al [19], Zhao et al [20], Li et al [21] and Ketenci et al [22]. Hashmi et al [30] has been presented comprehensive technique for detection of any type of image forgery.…”

Section: Related Workmentioning

confidence: 99%

Block and Fuzzy Techniques Based Forensic Tool for Detection and Classification of Image Forgery

Hashmi¹,

Keskar²

2015

Journal of Electrical Engineering and Technology

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-In today's era of advanced technological developments, the threats to the authenticity and integrity of digital images, in a nutshell, the threats to the Image Forensics Research communities have also increased proportionately. This happened as even for the 'non-expert' forgers, the availability of image processing tools has become a cakewalk. This image forgery poses a great problem for judicial authorities in any context of trade and commerce. Block matching based image cloning detection system is widely researched over the last 2-3 decades but this was discouraged by higher computational complexity and more time requirement at the algorithm level. Thus, for reducing time need, various dimension reduction techniques have been employed. Since a single technique cannot cope up with all the transformations like addition of noise, blurring, intensity variation, etc. we employ multiple techniques to a single image. In this paper, we have used Fuzzy logic approach for decision making and getting a global response of all the techniques, since their individual outputs depend on various parameters. Experimental results have given enthusiastic elicitations as regards various transformations to the digital image. Hence this paper proposes Fuzzy based cloning detection and classification system. Experimental results have shown that our detection system achieves classification accuracy of 94.12%. Detection accuracy (DAR) while in case of 81×81 sized copied portion the maximum accuracy achieved is 99.17% as regards subjection to transformations like Blurring, Intensity Variation and Gaussian Noise Addition.

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A Robust Method for Image Copy-Move Passive Forgery Detection with Enhanced Speed

Hassan

Sharma

2019

Proceedings of the International Conference on ISMAC in Computational Vision and Bio-Engineering 2018 (ISMAC-CVB)

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An efficient expanding block algorithm for image copy-move forgery detection

Cited by 106 publications

References 16 publications

Copy Move Image Forgery Detection Based on Polar Fourier Representation

Copy Move Image Forgery Detection Based on Polar Fourier Representation

Block and Fuzzy Techniques Based Forensic Tool for Detection and Classification of Image Forgery

A Robust Method for Image Copy-Move Passive Forgery Detection with Enhanced Speed

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