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CCE Faculty Articles
Automated Detection of Semagram-Laden Images Using Adaptive Neural Networks
Document Type
Article
Publication Title
Proceedings of SPIE
ISSN
0277-786X
Publication Date
4-23-2010
Abstract
Digital steganography has been used extensively for electronic copyright stamping, but also for criminal or covert activities. While a variety of techniques exist for detecting steganography the identification of semagrams, messages transmitted visually in a non-textual format remain elusive. The work that will be presented describes the creation of a novel application which uses hierarchical neural network architectures to detect the likely presence of a semagram message in an image. The application was used to detect semagrams containing Morse Code messages with over 80% accuracy. These preliminary results indicate a significant advance in the detection of complex semagram patterns.
DOI
10.1117/12.848474
NSUWorks Citation
Cannady, James D. Jr. and Cerkez, Paul S., "Automated Detection of Semagram-Laden Images Using Adaptive Neural Networks" (2010). CCE Faculty Articles. 446.
https://nsuworks.nova.edu/gscis_facarticles/446