Paper
5 October 2009 A real-time event classification system for a fibre-optic perimeter intrusion detection system
Seedahmed S. Mahmoud, Jim Katsifolis
Author Affiliations +
Proceedings Volume 7503, 20th International Conference on Optical Fibre Sensors; 75031P (2009) https://doi.org/10.1117/12.834159
Event: 20th International Conference on Optical Fibre Sensors, 2009, Edinburgh, United Kingdom
Abstract
The most important challenge for distributed fibre-optic intrusion detection systems is to minimise the nuisance alarm rate without compromising the system sensitivity. Event classification and discrimination is a powerful tool which can be used to minimise nuisance alarm rates whilst maintaining optimum sensitivity and probability of detection. A novel event classification system using supervised neural networks together with a level crossing based feature extraction algorithm is presented for a fence-based fibre-optic intrusion detection system. Performance results are presented showing accurate classification of and discrimination between different intrusion and non-intrusion events such as fence-climbing, fencecutting, stone-throwing and stick-dragging.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Seedahmed S. Mahmoud and Jim Katsifolis "A real-time event classification system for a fibre-optic perimeter intrusion detection system", Proc. SPIE 7503, 20th International Conference on Optical Fibre Sensors, 75031P (5 October 2009); https://doi.org/10.1117/12.834159
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Classification systems

Computer intrusion detection

Signal detection

Feature extraction

Detection and tracking algorithms

Sensors

Neural networks

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