Predicting Search Time in Visual Scenes using the Fuzzy Logic Approach
WAYNE STATE UNIV DETROIT MI DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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The mean search time of observers looking for targets in visual scenes with clutter is computed using the Fuzzy Logic Approach FLA. The FLA is presented by the authors as a robust method for the computation of search times and or probabilities of detection for signature management decisions. The MamdaniAssilian and Sugeno models have been investigated and are compared. A 44 image data set from TNO is used to build and validate the fuzzy logic model for detection. The input parameters are the local luminance. range, aspect, width. wavelet edge points and the single output is search ume. The MamdaniAssilian model gave predicted mean search times from data not used in the training set that had a 0.957 correlation to the field search times. The data set is reduced using a clustering method then modeled using the FLA and results are compared to experiment.
- Target Direction, Range and Position Finding