Computing Search Time in Visual Images Using the Fuzzy Logic Approach

Abstract : 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 in any part of the electromagnetic or acoustic spectrum. The Mamdani/Assilian and Sugeno models have been investigated and are compared. A 44 visual image data set from TNO is used to build and validate the fuzzy logic model for search time. The input parameters are the: local luminance range, aspect, width, wavelet edge points and the single output is search time. The Mamdani/Assilian 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.