Further Results on Texture Discrimination Based upon an Assumed Stochastic Texture Model.

Abstract

Further results of a new approach to texture discrimination are described. The approach is based upon an assumed stochastic model for texture in imagery and is an approximation to the statistically optimum maximum likelihood classifier. A method for estimating the structural parameters of the assumed stochastic texture model for each known texture class is described, and experimental results are provided which demonstrate the efficacy of this approach with simulated and real world texture data. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1981
Accession Number
ADA098106

Entities

People

  • Acie L. Vickers
  • James W. Modestino

Organizations

  • Rensselaer Polytechnic Institute

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Acquisition
  • Air Force
  • Computational Complexity
  • Discrimination
  • Discriminators
  • Engineering
  • Engineers
  • Estimators
  • Filters
  • Filtration
  • Frequency Response
  • Grids
  • Images
  • Models
  • Observation
  • Security
  • Two Dimensional

Readers

  • Computer Vision.
  • Statistical inference.