A classifier design for detecting fmage manipulations

Avcibaş, Ismail; Sevinç, Bayram; Memon, Nasir; Ramkumar, M.; Sankur, B.

doi:10.1109/icip.2004.1421647

Cited by 64 publications

(68 citation statements)

References 2 publications

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“…These regions are largely unaffected by varying JPEG compression qualities, and therefore exhibit little variation in the computed difference images, Equation (4). As such, these regions provide unreliable statistics and were ignored when computing the K-S statistic, Equation (5).…”

Section: Resultsmentioning

confidence: 99%

“…These include techniques for detecting cloning [1], [2]; splicing [3]; re-sampling artifacts [4], [5] ; color filter array aberrations [6]; disturbances of a camera's sensor noise pattern [7]; chromatic aberrations [8]; and lighting inconsistencies [9], [10], [11]. Although highly effective in some situations, many of these techniques are only applicable to relatively high quality images.…”

Section: Introductionmentioning

confidence: 99%

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Exposing Digital Forgeries From JPEG Ghosts

Farid

2009

IEEE Trans.Inform.Forensic Secur.

384

196

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Abstract-When creating a digital forgery, it is often necessary to combine several images, for example, when compositing one person's head onto another person's body. If these images were originally of different JPEG compression quality, then the digital composite may contain a trace of the original compression qualities. To this end, we describe a technique to detect if part of an image was initially compressed at a lower quality than the rest of the image. This approach is applicable to images of high and low quality and resolution.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Exposing Digital Forgeries From JPEG Ghosts

Farid

2009

IEEE Trans.Inform.Forensic Secur.

384

196

View full text Add to dashboard Cite

show abstract

“…Nonetheless, several methods have been proposed in the literature to identify it. Avcıbaş and others [4] designed a classifier able to discriminate between different kinds of manipulation (i.e. rotation, scaling, brightness adjustment and histogram equalization).…”

Section: Detecting Tampering Performed On a Single Imagementioning

confidence: 99%

Digital image forensics: a booklet for beginners

Redi

Taktak

Dugelay

2010

Multimed Tools Appl

307

115

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Digital visual media represent nowadays one of the principal means for communication. Lately, the reliability of digital visual information has been questioned, due to the ease in counterfeiting both its origin and content. Digital image forensics is a brand new research field which aims at validating the authenticity of images by recovering information about their history. Two main problems are addressed: the identification of the imaging device that captured the image, and the detection of traces of forgeries. Nowadays, thanks to the promising results attained by early studies and to the always growing number of applications, digital image forensics represents an appealing investigation domain for many researchers. This survey is designed for scholars and IT professionals approaching this field, reviewing existing tools and providing a view on the past, the present and the future of digital image forensics.

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“…Since light is an inseparable factor of an image, there are several techniques of dealing with fake or manipulated images in the literature or image forensic science based on light source direction, light intensity or shadow [8][9][10][11][12][13][14][15][16][17][18][19]. In an image, the brightness of a certain region of an image va− ries with the variations in the shape of the real object [8].…”

Section: Overview Of Image Forensic Techniquesmentioning

confidence: 99%

A novel method for detecting light source for digital images forensic

Roy

Mitra

Agrawal

2011

Opto-Electronics Review

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Manipulation in image has been in practice since centuries. These manipulated images are intended to alter facts — facts of ethics, morality, politics, sex, celebrity or chaos. Image forensic science is used to detect these manipulations in a digital image. There are several standard ways to analyze an image for manipulation. Each one has some limitation. Also very rarely any method tried to capitalize on the way image was taken by the camera. We propose a new method that is based on light and its shade as light and shade are the fundamental input resources that may carry all the information of the image. The proposed method measures the direction of light source and uses the light based technique for identification of any intentional partial manipulation in the said digital image. The method is tested for known manipulated images to correctly identify the light sources. The light source of an image is measured in terms of angle. The experimental results show the robustness of the methodology.

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A classifier design for detecting fmage manipulations

Cited by 64 publications

References 2 publications

Exposing Digital Forgeries From JPEG Ghosts

Exposing Digital Forgeries From JPEG Ghosts

Digital image forensics: a booklet for beginners

A novel method for detecting light source for digital images forensic

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