In the analog world, an image (specifically a photograph) has generally been accepted as a "proof of
occurrence" of the event it depicts. In today's digital age, however, the
creation and manipulation of digital images and videos are made simple
through digital processing tools that are easily and widely available. As a
consequence, we can no longer take the authenticity of images and videos for
granted, be they analog or digital. This is especially true when it comes to
legal evidence. Image and video forensics, in this context, is concerned
with uncovering some underlying fact about an image or video.
The past few years have seen a growth of research on image forensics. The work
has come to focus mainly on three types of problems:
Image origin/type identification. The goal is to determine through what means
a given digital image was originally generated, e.g., digital camera, scanner, computer graphics software, etc.
The most immediate challenge in this area is to discriminate computer generated images, which do not
depict real-life occurrences, from real images.
Image source identification.
Given the type of an image, this research area aims at identifying the class and/or individual characterisctics
of the mechanism that generated the digital image. This essentially entails associating the image with a class of sources that have
common characteristics (e.g., device model) and matching the image to an individual source device.
Image forgery detection. In this field of research, the objective is to determine whether a given digital image has
undergone any form of modification or processing after it was initially captured. Determining the processing history of an image and
identification of tampered image parts are the foremost research goals.
Research at ISIS has developed many techniques that address the three dimensions of the digital image forensics.
H. T. Sencar, and N. Memon, Overview of State-of-the-art in Digital Image Forensics,
Part of Indian Statistical Institute Platinum Jubilee Monograph series
titled 'Statistical Science and Interdisciplinary Research,' World
Scientific Press, (expected publication date) 2008. [BibTex]
S. Bayram, I. Avcibas, B. Sankur
and N. Memon, Image manipulation detection, Journal of Electronic
Imaging, 15(4) 041102, October-December 2006. [BibTex]
