Sensor Defects in Digital Image Forensic

Just as human fingerprints or skin blemishes can be used for forensic purposes, imperfections of digital imaging sensors can serve as unique identifiers in numerous forensic applications, such as matching an image to a specific camera, revealing malicious image manipulation and processing, and determining an approximate age of a digital photograph. There exist several different types of defects that are of interest to the forensic analysts caused by imperfections in manufacturing, physical processes occurring inside the camera, and by environmental factors. This chapter begins with analyzing the pixel defects, while pointing out their forensic potential. Then, specific problems are formulated as tasks involving detection or matching of defects and noise patterns. Practical algorithms for these tasks are developed within the framework of parameter estimation and signal detection theory. The performance of the algorithms is demonstrated in real world examples.

[1]  Nasir D. Memon,et al.  Improvements on Sensor Noise Based Source Camera Identification , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[2]  Orhan Bulan,et al.  Device temporal forensics: An information theoretic approach , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[3]  S. Kay Fundamentals of statistical signal processing: estimation theory , 1993 .

[4]  Miroslav Goljan,et al.  Using sensor pattern noise for camera model identification , 2008, 2008 15th IEEE International Conference on Image Processing.

[5]  Israel Koren,et al.  Identification of in-field defect development in digital image sensors , 2007, Electronic Imaging.

[6]  Roberto Caldelli,et al.  An analysis on attacker actions in fingerprint-copy attack in source camera identification , 2011, 2011 IEEE International Workshop on Information Forensics and Security.

[7]  Vito Cappellini,et al.  Analysis of denoising filters for photo response non uniformity noise extraction in source camera identification , 2009, 2009 16th International Conference on Digital Signal Processing.

[8]  Chang-Tsun Li,et al.  Source Camera Identification Using Enhanced Sensor Pattern Noise , 2009, IEEE Transactions on Information Forensics and Security.

[9]  Mo Chen,et al.  Defending Against Fingerprint-Copy Attack in Sensor-Based Camera Identification , 2011, IEEE Trans. Inf. Forensics Secur..

[10]  Mo Chen,et al.  Source digital camcorder identification using sensor photo response non-uniformity , 2007, Electronic Imaging.

[11]  Jan Lukás,et al.  Camera identification from printed images , 2008, Electronic Imaging.

[12]  Kannan Ramchandran,et al.  Low-complexity image denoising based on statistical modeling of wavelet coefficients , 1999, IEEE Signal Processing Letters.

[13]  Miroslav Goljan,et al.  Digital camera identification from sensor pattern noise , 2006, IEEE Transactions on Information Forensics and Security.

[14]  Jessica J. Fridrich,et al.  Camera identification from cropped and scaled images , 2008, Electronic Imaging.

[15]  Rainer Böhme,et al.  Can we trust digital image forensics? , 2007, ACM Multimedia.

[16]  Bülent Sankur,et al.  Blind identification of cellular phone cameras , 2007, Electronic Imaging.

[17]  Rainer Böhme,et al.  Synthesis of color filter array pattern in digital images , 2009, Electronic Imaging.

[18]  Steven Kay,et al.  Fundamentals Of Statistical Signal Processing , 2001 .

[19]  Mo Chen,et al.  Defending Against Fingerprint-Copy Attack in Sensor-Based Camera Identification , 2011, IEEE Transactions on Information Forensics and Security.

[20]  Hao Min,et al.  Modeling and estimation of FPN components in CMOS image sensors , 1998, Electronic Imaging.

[21]  Kenji Kurosawa,et al.  CCD fingerprint method-identification of a video camera from videotaped images , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[22]  Min Wu,et al.  Robust scanner identification based on noise features , 2007, Electronic Imaging.

[23]  Bülent Sankur,et al.  Blind Identification of Source Cell-Phone Model , 2008, IEEE Transactions on Information Forensics and Security.

[24]  Mo Chen,et al.  Digital imaging sensor identification (further study) , 2007, Electronic Imaging.

[25]  Thomas Gloe,et al.  Forensics for flatbed scanners , 2007, Electronic Imaging.

[26]  Craig R. Holt Two-channel likelihood detectors for arbitrary linear channel distortion , 1987, IEEE Trans. Acoust. Speech Signal Process..

[27]  Jan Lukás,et al.  Determining digital image origin using sensor imperfections , 2005, IS&T/SPIE Electronic Imaging.

[28]  Mo Chen,et al.  Imaging Sensor Noise as Digital X-Ray for Revealing Forgeries , 2007, Information Hiding.

[29]  Jan P. Allebach,et al.  Forensic classification of imaging sensor types , 2007, Electronic Imaging.

[30]  Mo Chen,et al.  Sensor noise camera identification: countering counter-forensics , 2010, Electronic Imaging.

[31]  Jessica J. Fridrich,et al.  Managing a large database of camera fingerprints , 2010, Electronic Imaging.

[32]  Stefan Katzenbeisser,et al.  Cell phone camera ballistics: attacks and countermeasures , 2010, Electronic Imaging.

[33]  J. Janesick,et al.  Scientific Charge-Coupled Devices , 2001 .

[34]  Greg J. Bloy Blind Camera Fingerprinting and Image Clustering , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[35]  Israel Koren,et al.  Quantitative analysis of in-field defects in image sensor arrays , 2007, 22nd IEEE International Symposium on Defect and Fault-Tolerance in VLSI Systems (DFT 2007).

[36]  Israel Koren,et al.  Automatic Detection of In-field Defect Growth in Image Sensors , 2008, 2008 IEEE International Symposium on Defect and Fault Tolerance of VLSI Systems.

[37]  Israel Koren,et al.  Characterization of Gain Enhanced In-Field Defects in Digital Imagers , 2009, 2009 24th IEEE International Symposium on Defect and Fault Tolerance in VLSI Systems.

[38]  Mo Chen,et al.  Determining Image Origin and Integrity Using Sensor Noise , 2008, IEEE Transactions on Information Forensics and Security.

[39]  Husrev T. Sencar,et al.  A study of the robustness of PRNU-based camera identification , 2009, Electronic Imaging.

[40]  Glenn Healey,et al.  Radiometric CCD camera calibration and noise estimation , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[41]  Mauro Barni,et al.  Exploring image dependencies: a new challenge in image forensics , 2010, Electronic Imaging.

[42]  Jan P. Allebach,et al.  Scanner identification using sensor pattern noise , 2007, Electronic Imaging.

[43]  Mo Chen,et al.  Identifying Common Source Digital Camera from Image Pairs , 2007, 2007 IEEE International Conference on Image Processing.

[44]  Gerald C. Holst,et al.  CCD arrays, cameras, and displays , 1996 .

[45]  Jessica J. Fridrich,et al.  Sensor-fingerprint based identification of images corrected for lens distortion , 2012, Other Conferences.

[46]  Nasir D. Memon,et al.  Efficient techniques for sensor fingerprint matching in large image and video databases , 2010, Electronic Imaging.