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Digital image forgery detection using passive techniques: A survey

Verifying the integrity of digital images and detecting the traces of tampering without using any protecting pre-extracted or pre-embedded information have become an important and hot research field. The popularity of this field and the rapid growth in papers published during the last years have put considerable need on creating a complete bibliography addressing published papers in this area. In this paper, an extensive list of blind methods for detecting image forgery is presented. By the word blind we refer to those methods that use only the image function. An attempt has been made to make this paper complete by listing most of the existing references and by providing a detailed classification group.

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A bibliography on blind methods for identifying image forgery

With the mushroom growth of state-of-the-art digital image and video manipulations tools, establishing the authenticity of multimedia content has become a challenging issue. Digital image forensics is an increasingly growing research field that symbolises a never ending struggle against forgery and tampering. This survey attempts to cover the blind techniques that have been proposed for exposing forgeries. This work dwells on the detection techniques for three of the most common forgery types, namely copy/move, splicing and retouching.

Survey on blind image forgery detection

With the development of easy-to-use and sophisticated image editing software, the alteration of the contents of digital images has become very easy to do and hard to detect. A digital image is a very rich source of information and can capture any event perfectly, but because of this reason, its authenticity is questionable. In this paper, a novel passive image forgery detection method is proposed based on local binary pattern (LBP) and discrete cosine transform (DCT) to detect copy–move and splicing forgeries. First, from the chrominance component of the input image, discriminative localized features are extracted by applying 2D DCT in LBP space. Then, support vector machine is used for detection. Experiments carried out on three image forgery benchmark datasets demonstrate the superiority of the method over recent methods in terms of detection accuracy.

/pdf/passive-detection-of-image-forgery-using-dct-and-local-17fr5qgd24.pdf

Passive detection of image forgery using DCT and local binary pattern

Digital image acquisition is now a simple task and information in the form of digital images is drastically increasing on social media, which has both positive and negative impacts on a society in many different ways. Advanced user-friendly tools have made it easy to manipulate image content in order to gain illegal advantage or to make false propaganda, and digital images and videos are not acceptable in courts of law as evidence without reliable forensic analysis. A lot of research has been done in order to address this problem and many techniques exist that detect and localize copy-move and splicing forgeries. However, it is very important to know whether these methods are robust, properly modelling the structural changes that have occurred in images due to copy-move and/or splicing forgeries, and can reliably classify a digital image as a genuine or modified image. In this paper, we present an extensive literature review of the state-of-the-art techniques on copy-move and splicing forgeries, highlight...

Copy-move and splicing image forgery detection and localization techniques: a review

To implement image splicing detection a blind, passive and effective splicing detection scheme was proposed in this paper. The model was based on moment features extracted from the multi-size block discrete cosine transform (MBDCT) and some image quality metrics (IQMs) extracted from the given test image, which are sensitive to spliced image. This model can measure statistical differences between original image and spliced image. Experimental results demonstrate that this new splicing detection algorithm is effective and reliable; indicating that the proposed approach has a broad application prospect.

An Effective Algorithm of Image Splicing Detection

With the advent of digital technology, digital image has gradually taken the place of the original analog photograph, and the forgery of digital image has become more and more easy and indiscoverable. Image splicing is a commonly used technique in image tampering. In this paper, we simply introduce the definition of image splicing and some methods of image splicing detection, mainly including the detection based on steganalysis model, the detection based on Hilbert-Huang transform (HHT) and moments of characteristic functions (CF) with wavelet decomposition. We focus on discussing our proposed approach based on image quality metrics (IQMs) and moment features. Especially we analyze the model creation and the extraction of features in digital image. In addition, we compare these approaches and analyze the future works of digital image forensics.

Study of Image Splicing Detection

Blind detection of image splicing based on image quality metrics and moment features: Blind detection of image splicing based on image quality metrics and moment features

Jiquan Kang

Papers

An Effective Algorithm of Image Splicing Detection

Study of Image Splicing Detection

Blind detection of image splicing based on image quality metrics and moment features: Blind detection of image splicing based on image quality metrics and moment features