DocumentCode
2349905
Title
Detecting hidden messages using higher-order statistical models
Author
Farid, Hany
Author_Institution
Dept. of Comput. Sci., Dartmouth Coll., Hanover, NH, USA
Volume
2
fYear
2002
fDate
2002
Abstract
Techniques for information hiding have become increasingly more sophisticated and widespread. With high-resolution digital images as carriers, detecting hidden messages has become considerably more difficult. This paper describes a new approach to detecting hidden messages in images. The approach uses a wavelet-like decomposition to build higher-order statistical models of natural images. A Fisher (1936) linear discriminant analysis is then used to discriminate between untouched and adulterated images.
Keywords
filtering theory; higher order statistics; image resolution; quadrature mirror filters; signal detection; wavelet transforms; Fisher linear discriminant analysis; hidden messages detection; high-resolution digital images; higher-order statistical models; information hiding; natural images; separable quadrature mirror filters; wavelet-like decomposition; Computer science; Digital images; Educational institutions; Filters; Higher order statistics; Image coding; Linear discriminant analysis; Statistical distributions; Steganography; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Image Processing. 2002. Proceedings. 2002 International Conference on
ISSN
1522-4880
Print_ISBN
0-7803-7622-6
Type
conf
DOI
10.1109/ICIP.2002.1040098
Filename
1040098
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