An artificial immune system based visual analysis model and its real-time terrain surveillance application

György Cserey, Wolfgang Porod, T. Roska

Research output: Contribution to journalArticle

9 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)250-262
Number of pages13
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3239
Publication statusPublished - 2004

Fingerprint

Artificial Immune System
Immune system
Model Analysis
Surveillance
Immune System
Color
Nonlinear networks
Real-time
Image Sequence
Textures
Hardware
Unknown
Pattern Analysis
Virtual Worlds
Color Image
Systems Analysis
Convert
Texture
Vision
Binary

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

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