Article
Automated Detection of Semagram-Laden Images Using Adaptive Neural Networks
Proceedings of SPIE
Document Type
Article
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
Disciplines
Citation Information
James D. Cannady and Paul S. Cerkez. "Automated Detection of Semagram-Laden Images Using Adaptive Neural Networks" Proceedings of SPIE (2010) ISSN: 0277-786X Available at: http://works.bepress.com/james-cannady/15/