Evaluation of Image Forgery Detection Using Multi-Scale Weber Local Descriptors

Hussain, Muhammad; Qasem, Sahar; Bebis, George; Muhammad, Ghulam; Aboalsamh, Hatim; Mathkour, Hassan

doi:10.1142/s0218213015400163

Cited by 41 publications

(26 citation statements)

References 15 publications

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“…In [23], a method using the Histogram of Oriented Gradients (HOG) is suggested to detect the copy-move forged regions. In [24], the multiscale Weber's law descriptor (multi-WLD) and multiscale LBP features are extracted for image splicing and copy-move forgery detection from chrominance components. The authors employed SVM for classifying an image as authentic or forged.…”

Section: Related Workmentioning

confidence: 99%

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Copy-Move Forgery Detection Technique for Forensic Analysis in Digital Images

Mahmood

Nawaz

Irtaza

et al. 2016

Mathematical Problems in Engineering

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Due to the powerful image editing tools images are open to several manipulations; therefore, their authenticity is becoming questionable especially when images have influential power, for example, in a court of law, news reports, and insurance claims. Image forensic techniques determine the integrity of images by applying various high-tech mechanisms developed in the literature. In this paper, the images are analyzed for a particular type of forgery where a region of an image is copied and pasted onto the same image to create a duplication or to conceal some existing objects. To detect the copy-move forgery attack, images are first divided into overlapping square blocks and DCT components are adopted as the block representations. Due to the high dimensional nature of the feature space, Gaussian RBF kernel PCA is applied to achieve the reduced dimensional feature vector representation that also improved the efficiency during the feature matching. Extensive experiments are performed to evaluate the proposed method in comparison to state of the art. The experimental results reveal that the proposed technique precisely determines the copy-move forgery even when the images are contaminated with blurring, noise, and compression and can effectively detect multiple copy-move forgeries. Hence, the proposed technique provides a computationally efficient and reliable way of copy-move forgery detection that increases the credibility of images in evidence centered applications.

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Section: Related Workmentioning

confidence: 99%

“…In this section, we take these into account and presented some experiments to show the robustness and accuracy of the algorithm. However, in [11,13,24,30], such experiments are not given. The forgery detection results are shown in Figures 5-7.…”

Section: Robustness and Accuracymentioning

confidence: 99%

Copy-Move Forgery Detection Technique for Forensic Analysis in Digital Images

Mahmood

Nawaz

Irtaza

et al. 2016

Mathematical Problems in Engineering

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“…Results show that the method gives better performance when compared to similar works. Hussain et al used multiscale Weber's law descriptor and multiscale Local Binary Pattern for copy move forgery detection [15]. Their method also applied Locally Learning Based (LLB) algorithm to reduce the dimension of feature space.…”

Section: Introductionmentioning

confidence: 99%

A New Copy Move Forgery Detection Method Resistant to Object Removal with Uniform Background Forgery

Ulutaş

Muzaffer

2016

Mathematical Problems in Engineering

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Users transfer large number of images everyday over the Internet. Easy to use commercial and open source image editing tools have made intactness of images questionable. Passive methods have been proposed in the literature to determine authenticity of images. However, a specific type of forgery called “Object Removal with uniform Background forgery” becomes a problem for keypoint based methods in the literature. In this paper, we proposed an effective copy move forgery detection technique. The method uses AKAZE features and nonlinear scale space for detection of copied/pasted regions. The proposed method detects “Object Removal with uniform Background” and “Replication” types of forgeries with high precision compared to similar works. Experimental results also indicate that the method yields better discriminative capability compared to others even if forged image has been rotated, blurred, AWGN added, or compressed by JPEG to hide clues of forgery.

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“…Recently, splicing direction methods applicable to color datasets are presented [16][17][18][19]. An image splicing detection algorithm using the run-length run-number and kernel PCA was presented [16].…”

Section: Introductionmentioning

confidence: 99%

“…However, this scheme requires an enormous of features and additional feature selection techniques to reduce the number of features. An image splicing detection method using multi-scale Weber local descriptors [18] was presented. This algorithm achieves high detection accuracies on three color image datasets for splicing forgery detection.…”

Section: Introductionmentioning

confidence: 99%

Image splicing detection based on inter-scale 2D joint characteristic function moments in wavelet domain

Park

Han

Moon

et al. 2016

J Image Video Proc.

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In this paper, we propose an image splicing detecting method using the characteristic function moments for the inter-scale co-occurrence matrix in the wavelet domain. We construct the co-occurrence matrices by using a pair of wavelet difference values across inter-scale wavelet subbands. In this process, we do not adopt the thresholding operation to prevent information loss. We extract the high-order characteristic function moments of the two-dimensional joint density function generated by the inter-scale co-concurrent matrices in order to detect image splicing forgery. Our method can be applied regardless of the color or gray image dataset using only luminance component of an image. By performing experimental simulations, we demonstrate that the proposed method achieves good performance in splicing detection. Our results show that the detection accuracy was greater than 95 % on average with well-known four splicing detection image datasets.

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Evaluation of Image Forgery Detection Using Multi-Scale Weber Local Descriptors

Cited by 41 publications

References 15 publications

Copy-Move Forgery Detection Technique for Forensic Analysis in Digital Images

Copy-Move Forgery Detection Technique for Forensic Analysis in Digital Images

A New Copy Move Forgery Detection Method Resistant to Object Removal with Uniform Background Forgery

Image splicing detection based on inter-scale 2D joint characteristic function moments in wavelet domain

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