Predicting Search Time in Visual Scenes 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. The Mamdani/Assilian 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 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.

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Document Details

Document Type
Technical Report
Publication Date
Jun 23, 2003
Accession Number
ADA583051

Entities

People

  • Abdelakrim Elgarhi
  • Euijung Sohn
  • Harpreet Singh
  • Thomas J. Meitzler

Organizations

  • Wayne State University

Tags

Communities of Interest

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

DTIC Thesaurus Topics

  • Acquisition
  • Clustering
  • Computational Processes
  • Computations
  • Data Sets
  • Detection
  • Detectors
  • Engineering
  • Fuzzy Logic
  • Fuzzy Sets
  • Identification Systems
  • Information Systems
  • Observers
  • Probability
  • Target Acquisition
  • Target Detection
  • Wavelet Transforms

Readers

  • Neural Network Machine Learning.
  • Sensor Fusion and Tracking Systems.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.