Detecting Digital Image Splicing in Chroma Spaces

Zhao, Xudong; Li, Jianhua; Li, Shenghong; Wang, Shilin

doi:10.1007/978-3-642-18405-5_2

Cited by 72 publications

(62 citation statements)

References 12 publications

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“…This method first computes edge-gradient array and then ARL along edge-gradient orientations. The forgery detection method proposed by Zhao et al [9] uses chrominance components and RLRN (run-length run-number). In this method, first the transformation is applied to convert RGB image into YCbCr color system.…”

Section: Realated Workmentioning

confidence: 99%

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Comparison between WLD and LBP descriptors for non-intrusive image forgery detection

Hussain¹,

Saleh

Aboalsamh

et al. 2014

2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings

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Abstract-Due to the availability of easy-to-use and powerful image editing tools, the authentication of digital images cannot be taken for granted and it gives rise to non-intrusive forgery detection problem because all imaging devices do not embed watermark. We investigated the detection of copy-move and splicing, the two harmful types of image forgery, using textural properties of images. Tampering distorts the texture micropatterns in an image and texture descriptors can be employed to detect tampering. We did comparative study to examine the effect of two state-of-the-art best texture descriptors: Multiscale Local Binary Pattern (Multi-LBP) and Multiscale Weber Law Descriptor (Multi-WLD). Multiscale texture descriptors extracted from the chrominance components of an image are passed to Support Vector Machine (SVM) to identify it as authentic or forged. The performance comparison reveals that Multi-WLD performs better than Multi-LBP in detecting copymove and splicing forgeries. Multi-WLD also outperforms stateof-the-art passive forgery detection techniques.

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Section: Realated Workmentioning

confidence: 99%

“…It follows that the traces of forgery are left in chrominance components. As such, the chrominance components are suitable for extracting features that are sensitive to tampering traces [9].…”

Section: A Convertiom From Rgb To Ycbcr Systemmentioning

confidence: 99%

Comparison between WLD and LBP descriptors for non-intrusive image forgery detection

Hussain¹,

Saleh

Aboalsamh

et al. 2014

2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings

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show abstract

“…In active approaches, additional information is inserted into the image before it is distributed. Digital watermarking is a prevalent active detection method [3]. Meanwhile, passive approaches modify the statistical features of images during image tampering [2].…”

Section: Introductionmentioning

confidence: 99%

Fractional Differential Texture Descriptors Based on the Machado Entropy for Image Splicing Detection

Ibrahim

Moghaddasi

Jalab

et al. 2015

Entropy

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Image splicing is a common operation in image forgery. Different techniques of image splicing detection have been utilized to regain people's trust. This study introduces a texture enhancement technique involving the use of fractional differential masks based on the Machado entropy. The masks slide over the tampered image, and each pixel of the tampered image is convolved with the fractional mask weight window on eight directions. Consequently, the fractional differential texture descriptors are extracted using the gray-level co-occurrence matrix for image splicing detection. The support vector machine is used as a classifier that distinguishes between authentic and spliced images. Results prove that the achieved improvements of the proposed algorithm are compatible with other splicing detection methods.

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“…Firstly, the edge-gradient array of a given image is calculated, and then the ARL is computed along the edge-gradient orientation. Zhao et al used chrominance spaces with RLRN (run-length run-number) for CMF detection [7]. The input color image is transformed into the YCbCr color mode.…”

Section: Introductionmentioning

confidence: 99%

“…YCbCr color space stores the color in terms of its luminance and chrominance. The human eyes are less sensitive to chrominance than luminance; however, even a tampered image looks natural, some tampered traces are left in the chrominance channels [7]. In the second step, the chrominance component (either Cb or Cr) is used to extract image features in the form of Weber local descriptors (WLD) [13].…”

mentioning

confidence: 99%

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

Saleh

Hussain

Muhammad

et al. 2013

Advances in Visual Computing

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Abstract. In this paper, a detailed evaluation of multi-scale Weber local descriptors (WLD) based image forgery detection method is presented. Multiscale WLD extracts the features from chrominance components of an image, which usually encode the tampering information that escapes the human eyes. The WLD incorporates differential excitation and gradient orientation of a center pixel around a neighborhood. In the multi-scale WLD, three different neighborhoods are chosen. A support vector machine is used for classification purpose. The experiments are conducted on three image databases, namely, CASIA v1.0, CASIA v2.0, and Columbia color. The experimental results show that the accuracy rate of the proposed method are 94.19% for CASIA v1.0, 96.61% for CASIA v2.0, and 94.17% for Columbia dataset. These accuracies are significantly higher than those obtained by some state-of-the-art methods.

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Detecting Digital Image Splicing in Chroma Spaces

Cited by 72 publications

References 12 publications

Comparison between WLD and LBP descriptors for non-intrusive image forgery detection

Comparison between WLD and LBP descriptors for non-intrusive image forgery detection

Fractional Differential Texture Descriptors Based on the Machado Entropy for Image Splicing Detection

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

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