Digital single lens reflex camera identification from traces of sensor dust

Ahmet Emir Dirik; Husrev Taha Senear; Nasir Memon

doi:10.1109/TIFS.2008.926987

Digital single lens reflex camera identification from traces of sensor dust

Ahmet Emir Dirik, Husrev Taha Senear, Nasir Memon

Center for Cyber Security

Research output: Contribution to journal › Article › peer-review

Abstract

Digital single lens reflex cameras suffer from a well-known sensor dust problem due to interchangeable lenses that they deploy. The dust particles that settle in front of the imaging sensor create a persistent pattern in all captured images. In this paper, we propose a novel source camera identification method based on detection and matching of these dust-spot characteristics. Dust spots in the image are detected based on a (Gaussian) intensity loss model and shape properties. To prevent false detections, lens parameter-dependent characteristics of dust spots are also taken into consideration. Experimental results show that the proposed detection scheme can be used in identification of the source digital single lens reflex camera at low false positive rates, even under heavy compression and downsampling.

Original language	English (US)
Article number	4558161
Pages (from-to)	539-552
Number of pages	14
Journal	IEEE Transactions on Information Forensics and Security
Volume	3
Issue number	3
DOIs	https://doi.org/10.1109/TIFS.2008.926987
State	Published - Sep 2008

Keywords

Digital forensics
Digital single lens reflex (DSLR)
Sensor dust

ASJC Scopus subject areas

Safety, Risk, Reliability and Quality
Computer Networks and Communications

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10.1109/TIFS.2008.926987

Cite this

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title = "Digital single lens reflex camera identification from traces of sensor dust",

abstract = "Digital single lens reflex cameras suffer from a well-known sensor dust problem due to interchangeable lenses that they deploy. The dust particles that settle in front of the imaging sensor create a persistent pattern in all captured images. In this paper, we propose a novel source camera identification method based on detection and matching of these dust-spot characteristics. Dust spots in the image are detected based on a (Gaussian) intensity loss model and shape properties. To prevent false detections, lens parameter-dependent characteristics of dust spots are also taken into consideration. Experimental results show that the proposed detection scheme can be used in identification of the source digital single lens reflex camera at low false positive rates, even under heavy compression and downsampling.",

keywords = "Digital forensics, Digital single lens reflex (DSLR), Sensor dust",

author = "Dirik, {Ahmet Emir} and Senear, {Husrev Taha} and Nasir Memon",

note = "Funding Information: Manuscript received June 30, 2008; revised April 15, 2008. First published July 9, 2008; last published August 13, 2008 (projected). This work was supported by the National Institute of Justice under Grant 2006-92251-NY-IJ. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Jessica J. Fridrich.",

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doi = "10.1109/TIFS.2008.926987",

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volume = "3",

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AU - Dirik, Ahmet Emir

AU - Senear, Husrev Taha

AU - Memon, Nasir

N1 - Funding Information: Manuscript received June 30, 2008; revised April 15, 2008. First published July 9, 2008; last published August 13, 2008 (projected). This work was supported by the National Institute of Justice under Grant 2006-92251-NY-IJ. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Jessica J. Fridrich.

PY - 2008/9

Y1 - 2008/9

N2 - Digital single lens reflex cameras suffer from a well-known sensor dust problem due to interchangeable lenses that they deploy. The dust particles that settle in front of the imaging sensor create a persistent pattern in all captured images. In this paper, we propose a novel source camera identification method based on detection and matching of these dust-spot characteristics. Dust spots in the image are detected based on a (Gaussian) intensity loss model and shape properties. To prevent false detections, lens parameter-dependent characteristics of dust spots are also taken into consideration. Experimental results show that the proposed detection scheme can be used in identification of the source digital single lens reflex camera at low false positive rates, even under heavy compression and downsampling.

AB - Digital single lens reflex cameras suffer from a well-known sensor dust problem due to interchangeable lenses that they deploy. The dust particles that settle in front of the imaging sensor create a persistent pattern in all captured images. In this paper, we propose a novel source camera identification method based on detection and matching of these dust-spot characteristics. Dust spots in the image are detected based on a (Gaussian) intensity loss model and shape properties. To prevent false detections, lens parameter-dependent characteristics of dust spots are also taken into consideration. Experimental results show that the proposed detection scheme can be used in identification of the source digital single lens reflex camera at low false positive rates, even under heavy compression and downsampling.

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KW - Digital single lens reflex (DSLR)

KW - Sensor dust

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Digital single lens reflex camera identification from traces of sensor dust

Abstract

Keywords

ASJC Scopus subject areas

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