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Proceedings Paper

Intelligent security system based on neuro-fuzzy multisensor data fusion
Author(s): Judy Chen; Andrew A. Kostrzewski; Dai Hyun Kim; Yih-Shi Kuo; Gajendra D. Savant; Barney B. Roberts
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Paper Abstract

This paper presents a real-world application of neurofuzzy processing to a security system with multiple sensor. Integrating fuzzy logic with neural networks, the authors have automated the tasks of sensor data fusion and determination of false/true alarms, which currently rely solely on human monitoring operators, so that they operate in a way similar to human reasoning. This integrated security system includes a set of heterogeneous sensor. To take advantage of each sensor's strengths, they are positioned and integrated for side, accurate, economical coverage. The system includes real-time tracking cameras functioning as true digital motion detectors with the capability of approximating the size, direction, and number of intruders. The system is also capable of real-time image segmentation based on motion, and of image recognition based on neural networks.

Paper Details

Date Published: 13 October 1998
PDF: 8 pages
Proc. SPIE 3455, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, (13 October 1998); doi: 10.1117/12.326708
Show Author Affiliations
Judy Chen, Physical Optics Corp. (United States)
Andrew A. Kostrzewski, Physical Optics Corp. (United States)
Dai Hyun Kim, Physical Optics Corp. (United States)
Yih-Shi Kuo, Physical Optics Corp. (United States)
Gajendra D. Savant, Physical Optics Corp. (United States)
Barney B. Roberts, U.S. Army Missile Command (United States)

Published in SPIE Proceedings Vol. 3455:
Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation
Bruno Bosacchi; David B. Fogel; James C. Bezdek, Editor(s)

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