Predicting search time in visually cluttered scenes using the fuzzy logic approach

The mean search time of observers searching for targets in visual scenes wi th clutter is computed using the fuzzy logic approach (FLA). The FLA is pre sented as a robust method for the computation of search times and/or probab ilities of detection for treated vehicles. The Mamdani/Assilian and Sugeno models have been investigated and are compared. The Search_2 dataset from T NO is used to build and validate the fuzzy logic approach for target detect ion modeling. The input parameters are: local luminance, range, aspect, wid th, and wavelet edge points, and the single output is search time. The Mamd ani/Assilian model gave predicted mean search times for data not used in th e 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. (C) 2001 Society of Photo-Optical I nstrumentation Engineers.