1 July 1998 Computing the probability of target detection in dynamic visual scenes containing clutter using fuzzy logic approach
Thomas J. Meitzler, Regina W. Kistner, William T. Pibil, Eui Jung Sohn, Darryl Bryk, David Bednarz
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The probability of detection (Pd) of moving targets in visually cluttered scenes is computed using the fuzzy logic approach (FLA). The FLA is presented as a robust method for the computation and prediction of the Pd of targets in cluttered scenes with sparse data. A limited data set of visual imagery is used to model the relationships between several input parameters: the contrast, vehicle camouflage, range, aspect, width, and experimental Pd. The fuzzy and neurofuzzy models provide predicted Pd values that have 0.9 correlation with the experimental Pd's. The results obtained indicate the robustness of the fuzzy-based modeling techniques and the potential applicability of the FLA to those types of problems that have to do with the modeling of aided or unaided detection of a signal (acoustic, electromagnetic) in any spectral regime.
Thomas J. Meitzler, Regina W. Kistner, William T. Pibil, Eui Jung Sohn, Darryl Bryk, and David Bednarz "Computing the probability of target detection in dynamic visual scenes containing clutter using fuzzy logic approach," Optical Engineering 37(7), (1 July 1998). https://doi.org/10.1117/1.601847
Published: 1 July 1998
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Cited by 3 scholarly publications.
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KEYWORDS
Target detection

Data modeling

Fuzzy logic

Visualization

Target acquisition

Detection and tracking algorithms

Optical engineering

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