16 June 1997 Computing the probability of target detection in infrared and visual scenes using the fuzzy logic approach
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Proceedings Volume 3063, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing VIII; (1997); doi: 10.1117/12.276071
Event: AeroSense '97, 1997, Orlando, FL, United States
Abstract
The probability of detection (Pd) of targets in infrared and visually cluttered scenes is computed using the Fuzzy Logic Approach (FLA). The FLA is presented by the authors as a robust and high fidelity method for the computation and prediction of the Pd of targets. The Mamdani/Assilian, Sugeno and Neurofuzzy-based models have been investigated. A limited data set of visual imagery has been used to model the relationships between several input parameters; the contrast, camouflage condition, range, aspect, width, and experimental Pd. The fuzzy and neuro-fuzzy models gave predicted Pd values that had 0.98 correlation to the experimental Pd's. The results obtained indicate the robustness of the fuzzy-based modeling techniques and the applicability of the FLA to those types of problems having to do with the modeling of human object detection and perception in any spectral regime.
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Thomas J. Meitzler, Harpreet Singh, Labib Arefeh, Grant R. Gerhart, Eui Jung Sohn, "Computing the probability of target detection in infrared and visual scenes using the fuzzy logic approach", Proc. SPIE 3063, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing VIII, (16 June 1997); doi: 10.1117/12.276071; https://doi.org/10.1117/12.276071
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KEYWORDS
Fuzzy logic

Palladium

Visualization

Target detection

Data modeling

Visual process modeling

Systems modeling

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