Abstract
We present a real-time visual analysis system for surveillance applications based on an Artificial Immune System inspired framework [10] that can reliably detect unknown patterns in input image sequences. The system converts gray-scale or color images to binary with statistical 3x3 sub-pattern analysis based on an AIS algorithm, which make use of the standard AIS modules. Our system is implemented on specialized hardware (the Cellular Nonlinear Network (CNN) Universal Machine). Results from tests in a 3D virtual world with different terrain textures are reported to demonstrate that the system can detect unknown patterns and dynamical changes in image sequences. Applications of the system include in particular explorer systems for terrain surveillance.
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Cserey, G., Porod, W., Roska, T. (2004). An Artificial Immune System Based Visual Analysis Model and Its Real-Time Terrain Surveillance Application. In: Nicosia, G., Cutello, V., Bentley, P.J., Timmis, J. (eds) Artificial Immune Systems. ICARIS 2004. Lecture Notes in Computer Science, vol 3239. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30220-9_21
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DOI: https://doi.org/10.1007/978-3-540-30220-9_21
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