BIB-VERSION:: CS-TR-v2.0
ID:: ncstrl.dartmouthcs//TR2005-557
ENTRY:: February 16, 2008
ORGANIZATION:: Dartmouth College, Computer Science
TITLE:: Natural Image Statistics for Digital Image Forensics
TYPE:: Technical Report (paper)
REVISION:: 1
AUTHOR:: Lyu, Siwei
DATE:: August 2005
RETRIEVAL:: For a paper copy, email <reports@cs.dartmouth.edu>
RETRIEVAL:: For a paper copy, write to
       Technical Report Librarian
       Department of Computer Science
       Dartmouth College
       6211 Sudikoff Laboratory
       Hanover, NH 03755-3510
       USA
RETRIEVAL:: PDF at http://www.cs.dartmouth.edu/reports/TR2005-557.pdf
ABSTRACT:: 
We describe a set of natural image statistics that are built upon two
multi-scale image decompositions, the quadrature mirror filter pyramid
decomposition and the local angular harmonic decomposition. These
image statistics consist of first- and higher-order statistics that
capture certain statistical regularities of natural images. We propose
to apply these image statistics, together with classification
techniques, to three problems in digital image forensics: (1)
differentiating photographic images from computer-generated
photorealistic images, (2) generic steganalysis; (3) rebroadcast image
detection. We also apply these image statistics to the traditional
art authentication for forgery detection and identification of artists
in an art work. For each application we show the effectiveness of these
image statistics and analyze their sensitivity and robustness.
NOTE:: 
Ph.D dissertation.  Advisor: Hany Farid.
END:: ncstrl.dartmouthcs//TR2005-557