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Proceedings Paper

Automated detection of semagram-laden images using adaptive neural networks
Author(s): Paul S. Cerkez; James D. Cannady
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Paper 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.

Paper Details

Date Published: 28 April 2010
PDF: 12 pages
Proc. SPIE 7708, Mobile Multimedia/Image Processing, Security, and Applications 2010, 77080M (28 April 2010); doi: 10.1117/12.848474
Show Author Affiliations
Paul S. Cerkez, Nova Southeastern Univ. (United States)
DCS Corp. (United States)
James D. Cannady, Nova Southeastern Univ. (United States)


Published in SPIE Proceedings Vol. 7708:
Mobile Multimedia/Image Processing, Security, and Applications 2010
Sos S. Agaian; Sabah A. Jassim, Editor(s)

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