A Maximum Likelihood Approach to Texture Classification

Authors:
A. L. Vickers;J. W. Modestino
Affiliations:
Department of Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY 12181.;Department of Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY 12181.
Venue:
IEEE Transactions on Pattern Analysis and Machine Intelligence
Year:
1982

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Abstract

A new approach to texture classification is described which is based on measurements of the spatial gray-level co-occurrence probability matrix. This approach can make use of assumed stochastic models for texture in imagery and is an approximation to the statistically optimum maximum likelihood classifier. The efficacy of the approach is demonstrated through experimental results obtained with real-world texture data.