Improving source camera identification using a simplified total variation based noise removal algorithm

Gisolf, Floris; Malgoezar, A.M.N.; Baar, Teun; Geradts, Zeno

doi:10.1016/j.diin.2013.08.002

Cited by 32 publications

(37 citation statements)

References 12 publications

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“…In this paper, we use the wavelet based denoising filter as described in our prior work [1,7,10,17]. Assuming the following linearized sensor model for the residual [2,16,9], 1…”

Section: Preliminariesmentioning

confidence: 99%

Effect of Compression on Sensor-Fingerprint Based Camera Identification

Goljan¹,

Chen²,

Comesaña³

et al. 2016

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Camera identification using sensor fingerprints is nowadays a well-established technology for reliably linking an image or a video clip to a specific camera. The sensor fingerprint is typically estimated from images (video frames) provably taken by the imaging device. An image or a video clip is then associated with the fingerprint when some form of a matched filter exceeds a certain threshold, which is set to achieve a prescribed false alarm. However, when the images from which the sensor fingerprint is estimated are lossy compressed, the statistical properties of the detection statistic change, which requires an adjustment of the decision threshold to guarantee the same false-alarm rate. In this paper, we study this effect both theoretically and experimentally. A very good match between the theoretical and experimental results validates our approach. This study is especially important for video forensic because of the higher compression rates.

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“…In this paper, we use the wavelet based denoising filter as described in our prior work [1,7,10,17]. Assuming the following linearized sensor model for the residual [2,16,9], 1…”

Section: Preliminariesmentioning

confidence: 99%

Effect of Compression on Sensor-Fingerprint Based Camera Identification

Goljan¹,

Chen²,

Comesaña³

et al. 2016

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“…With the use of Camera Identification based on Photo Response Non-Uniformity, new links can be made with cameras [27]. Also other databases such as biometric databases of faces and other body features could be linked in the future.…”

Section: Integrated Forensic Platform Projects At the Netherlands Formentioning

confidence: 99%

The interface between forensic science and technology: how technology could cause a paradigm shift in the role of forensic institutes in the criminal justice system

Kloosterman

Mapes

Geradts

et al. 2015

Phil. Trans. R. Soc. B

Self Cite

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In this paper, the importance of modern technology in forensic investigations is discussed. Recent technological developments are creating new possibilities to perform robust scientific measurements and studies outside the controlled laboratory environment. The benefits of real-time, on-site forensic investigations are manifold and such technology has the potential to strongly increase the speed and efficacy of the criminal justice system. However, such benefits are only realized when quality can be guaranteed at all times and findings can be used as forensic evidence in court. At the Netherlands Forensic Institute, innovation efforts are currently undertaken to develop integrated forensic platform solutions that allow for the forensic investigation of human biological traces, the chemical identification of illicit drugs and the study of large amounts of digital evidence. These platforms enable field investigations, yield robust and validated evidence and allow for forensic intelligence and targeted use of expert capacity at the forensic institutes. This technological revolution in forensic science could ultimately lead to a paradigm shift in which a new role of the forensic expert emerges as developer and custodian of integrated forensic platforms.

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“…Floris Gisolf et al [17] propose a simplified total variation based noise removal algorithm for maximize the speed of PRNU extraction without losing accuracy as compared to wavelet based denoising. The result show that extraction is about 3.5 times faster with propose algorithm as compared to wavelet based denoising.…”

Section: Use Of Sensor Imperfectionmentioning

confidence: 99%

Approaches for Camera Source Identification: A Review

Khapare¹

2017

ijecs

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Identifying the characteristics and the originality of the any digital device has become more important in today's digital world using digital forensics. This survey paper studies the recent developments in the field of image source identification. Proposed methods in the literature are divided into five broad areas based on source identification using Metadata (Exif), Image Features, CFA and Demos icing Artifacts, Lens Distortions and Wavelet Transforms. The methods and algorithm of the proposed approaches in each category is described in detail to use accurate technique in source camera identification.

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Improving source camera identification using a simplified total variation based noise removal algorithm

Cited by 32 publications

References 12 publications

Effect of Compression on Sensor-Fingerprint Based Camera Identification

Effect of Compression on Sensor-Fingerprint Based Camera Identification

The interface between forensic science and technology: how technology could cause a paradigm shift in the role of forensic institutes in the criminal justice system

Approaches for Camera Source Identification: A Review

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