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Optical Engineering

Predicting the probability of target detection in static infrared and visual scenes using the fuzzy logic approach
Author(s): Thomas J. Meitzler; Eui Jung Sohn; Grant R. Gerhart; Harpreet Singh; Labib Arefeh
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Paper Abstract

The probability of detection (Pd) of targets in static infrared and 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. The Mamdani/Assilian and Sugeno neuro-fuzzy-based models are investigated. A large set of infrared (IR) imagery and a limited set of visual imagery are 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-in-the-loop target detection in any spectral regime.

Paper Details

Date Published: 1 January 1998
PDF: 8 pages
Opt. Eng. 37(1) doi: 10.1117/1.601849
Published in: Optical Engineering Volume 37, Issue 1
Show Author Affiliations
Thomas J. Meitzler, U.S. Army Tank-Automotive Command (United States)
Eui Jung Sohn, U.S. Army Tank-Automotive Command (United States)
Grant R. Gerhart, U.S. Army Tank-Automotive Command (United States)
Harpreet Singh, Wayne State Univ. (United States)
Labib Arefeh, College of Engineering and Technology (Israel)

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