Predicting Search Time in Visually Cluttered Scenes Using the Fuzzy Logic Approach

Abstract

The mean search time of observers searching for targets in visual scenes with clutter is computed using the Fuzzy Logic Approach (FLA). The FLA is presented as a robust method for the computation of search times and or probabilities of detection for signature management decisions. The Mamdani/Assilian and Sugeno models have been investigated and are compared. The Search_2 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 time. The Mamdani/Assilian model gave predicted mean search times for 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.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2001
Accession Number
ADA484818

Entities

People

  • Abdelakrim Elgarhi
  • Deok H. Nam
  • Euijung Sohn
  • Harpreet Singh
  • Thomas Meitzler

Organizations

  • Tank-automotive and Armaments Command

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Acquisition
  • Clustering
  • Computational Processes
  • Data Analysis
  • Data Sets
  • Detection
  • Detectors
  • Fuzzy Logic
  • Fuzzy Sets
  • Identification Systems
  • Information Systems
  • Logic
  • Probability
  • Set Theory
  • Target Acquisition
  • Training
  • Wavelet Transforms

Readers

  • Artificial Intelligence
  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.