Detecting image forgeries using metrology

Image forgery technology has become popular for tampering with digital photography. This paper presents a framework for detecting fake regions using single view metrology and enforcing geometric constraints from shadows. In particular, we describe how to (1) estimate the region of interest’s 3D measurements from a single perspective view of a scene given only minimal geometric information determined from the image, (2) determine the fake region by exploring the imaged shadow relations that are modeled by the planar homology. We also show that image forgery on the vertical plane or arbitrary plane can be detected through the measurement on such plane. Our approach efficiently extracts geometric constraints from a single image and makes use of them for the digital forgery detection. Experimental results on both the synthetic data against noise and visually plausible images demonstrate the performance of the proposed method.

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

[2]  Jessica Fridrich,et al.  Detection of Copy-Move Forgery in Digital Images , 2004 .

[3]  Hany Farid,et al.  Exposing digital forgeries by detecting traces of resampling , 2005, IEEE Transactions on Signal Processing.

[4]  Tomás Pevný,et al.  Detection of Double-Compression in JPEG Images for Applications in Steganography , 2008, IEEE Transactions on Information Forensics and Security.

[5]  Luc Van Gool,et al.  Planar homologies as a basis for grouping and recognition , 1998, Image Vis. Comput..

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

[7]  Mahalingam Ramkumar,et al.  A classifier design for detecting image manipulations , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[8]  Wei Su,et al.  Image splicing detection using 2-D phase congruency and statistical moments of characteristic function , 2007, Electronic Imaging.

[9]  H. Farid A Survey of Image Forgery Detection , 2008 .

[10]  Nasir D. Memon,et al.  Source camera identification based on CFA interpolation , 2005, IEEE International Conference on Image Processing 2005.

[11]  Hany Farid,et al.  Detecting Photographic Composites of People , 2008, IWDW.

[12]  Micah K. Johnson,et al.  Metric Measurements on a Plane from a Single Image , 2006 .

[13]  Hany Farid,et al.  Exposing digital forgeries through chromatic aberration , 2006, MM&Sec '06.

[14]  Xiaochun Cao,et al.  Camera Calibration Using Symmetric Objects , 2006, IEEE Transactions on Image Processing.

[15]  Shih-Fu Chang,et al.  A model for image splicing , 2004, 2004 International Conference on Image Processing, 2004. ICIP '04..

[16]  Min Wu,et al.  Digital image forensics via intrinsic fingerprints , 2008, IEEE Transactions on Information Forensics and Security.

[17]  Rongrong Wang,et al.  Detecting doctored images using camera response normality and consistency , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[18]  Andrew Zisserman,et al.  Metric rectification for perspective images of planes , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[19]  Martin F. H. Schuurmans,et al.  Digital watermarking , 2002, Proceedings of ASP-DAC/VLSI Design 2002. 7th Asia and South Pacific Design Automation Conference and 15h International Conference on VLSI Design.

[20]  Xiaochun Cao,et al.  Detecting photographic composites using two-view geometrical constraints , 2009, 2009 IEEE International Conference on Multimedia and Expo.

[21]  Babak Mahdian,et al.  Detection of copy-move forgery using a method based on blur moment invariants. , 2007, Forensic science international.

[22]  Weihong Wang,et al.  Detecting Re-projected Video , 2008, Information Hiding.

[23]  Min Wu,et al.  Noise Features for Image Tampering Detection and Steganalysis , 2007, 2007 IEEE International Conference on Image Processing.

[24]  Jan Lukás,et al.  Estimation of Primary Quantization Matrix in Double Compressed JPEG Images , 2003 .

[25]  Hany Farid,et al.  Exposing digital forgeries by detecting inconsistencies in lighting , 2005, MM&Sec '05.

[26]  Hassan Foroosh,et al.  View-Invariant Action Recognition from Point Triplets , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  Alin C. Popescu,et al.  Exposing Digital Forgeries by Detecting Duplicated Image Regions Exposing Digital Forgeries by Detecting Duplicated Image Regions , 2004 .

[28]  Larry S. Davis,et al.  Segmentation of Planar Objects and Their Shadows in Motion Sequences , 2006, International Journal of Computer Vision.

[29]  Shih-Fu Chang,et al.  Image Splicing Detection using Camera Response Function Consistency and Automatic Segmentation , 2007, 2007 IEEE International Conference on Multimedia and Expo.

[30]  Zhanyi Hu,et al.  Single view metrology from scene constraints , 2005, Image Vis. Comput..

[31]  Mary J. Bravo,et al.  Image forensic analyses that elude the human visual system , 2010, Electronic Imaging.

[32]  Hany Farid,et al.  Exposing digital forgeries by detecting traces of resampling , 2005 .

[33]  Hany Farid,et al.  Exposing Digital Forgeries in Complex Lighting Environments , 2007, IEEE Transactions on Information Forensics and Security.

[34]  H. Farid,et al.  Image forgery detection , 2009, IEEE Signal Processing Magazine.

[35]  Bernhard P. Wrobel,et al.  Multiple View Geometry in Computer Vision , 2001 .

[36]  Ian D. Reid,et al.  Single View Metrology , 2000, International Journal of Computer Vision.

[37]  Shih-Fu Chang,et al.  Blind detection of photomontage using higher order statistics , 2004, 2004 IEEE International Symposium on Circuits and Systems (IEEE Cat. No.04CH37512).

[38]  Siwei Lyu,et al.  How realistic is photorealistic? , 2005, IEEE Transactions on Signal Processing.