Using vanishing points for camera calibration
International Journal of Computer Vision
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Exposing digital forgeries by detecting inconsistencies in lighting
MM&Sec '05 Proceedings of the 7th workshop on Multimedia and security
Exposing digital forgeries through chromatic aberration
MM&Sec '06 Proceedings of the 8th workshop on Multimedia and security
Scene completion using millions of photographs
ACM SIGGRAPH 2007 papers
Seam carving for content-aware image resizing
ACM SIGGRAPH 2007 papers
Photoshop cs3 photo effects cookbook
Photoshop cs3 photo effects cookbook
Detecting Photographic Composites of People
IWDW '07 Proceedings of the 6th International Workshop on Digital Watermarking
Generating photo manipulation tutorials by demonstration
ACM SIGGRAPH 2009 papers
The Digital Photography Book, Volume 2
The Digital Photography Book, Volume 2
Interactive reflection editing
ACM SIGGRAPH Asia 2009 papers
Multi-scale image harmonization
ACM SIGGRAPH 2010 papers
Scene illumination as an indicator of image manipulation
IH'10 Proceedings of the 12th international conference on Information hiding
Exposing digital forgeries by detecting traces of resampling
IEEE Transactions on Signal Processing
Exposing digital forgeries in color filter array interpolated images
IEEE Transactions on Signal Processing - Part II
Exposing Digital Forgeries in Complex Lighting Environments
IEEE Transactions on Information Forensics and Security - Part 1
Digital camera identification from sensor pattern noise
IEEE Transactions on Information Forensics and Security
Format based photo forgery image detection
Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
Inverse image editing: recovering a semantic editing history from a before-and-after image pair
ACM Transactions on Graphics (TOG)
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The advent of sophisticated photo editing software has made it increasingly easier to manipulate digital images. Often visual inspection cannot definitively distinguish the resulting forgeries from authentic photographs. In response, forensic techniques have emerged to detect geometric or statistical inconsistencies that result from specific forms of photo manipulation. In this article we describe a new forensic technique that focuses on geometric inconsistencies that arise when fake reflections are inserted into a photograph or when a photograph containing reflections is manipulated. This analysis employs basic rules of reflective geometry and linear perspective projection, makes minimal assumptions about the scene geometry, and only requires the user to identify corresponding points on an object and its reflection. The analysis is also insensitive to common image editing operations such as resampling, color manipulations, and lossy compression. We demonstrate this technique with both visually plausible forgeries of our own creation and commercially produced forgeries.