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13 October 1998 Intelligent security system based on neuro-fuzzy multisensor data fusion
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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.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Judy Chen, Andrew A. Kostrzewski, Dai Hyun Kim, Yih-Shi Kuo, Gajendra D. Savant, and Barney B. Roberts "Intelligent security system based on neuro-fuzzy multisensor data fusion", Proc. SPIE 3455, Applications and Science of Neural Networks, Fuzzy Systems, and Evolutionary Computation, (13 October 1998); https://doi.org/10.1117/12.326708
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