TEXTURE DISCRIMINATION BASED UPON AN ASSUMED STOCHASTIC TEXTURE MODEL.

J. W. Modestino, R. W. Fries, A. L. Vickers

Research output: Contribution to journalConference article

2 Scopus citations

Abstract

A new approach to texture discrimination is described. This approach is based upon an assumed stochastic model for texture in imagery and is an approximation to the statistically optimum maximum likelihood classifier. The construction and properties of the stochastic texture model are described and a digital filtering implementation of the resulting maximum likelihood texture discriminant is provided. The efficacy of this approach is demonstrated through experimental results obtained with simulated texture data. A comparison is provided with more conventional texture discriminants under identical conditions. The implications to texture discrimination in real-world imagery are discussed.

Original languageEnglish (US)
Pages (from-to)79-84
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume1
DOIs
StatePublished - Jan 1 1979
EventProc IEEE Conf Decis Control Incl Symp Adapt Processes 18th - Fort Lauderdale, FL, USA
Duration: Dec 12 1979Dec 14 1979

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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