Title :
A Maximum Likelihood Approach to Texture Classification
Author :
Vickers, A.L. ; Modestino, J.W.
Author_Institution :
Department of Electrical, Computer and Systems Engineering, Rensselaer Polytechnic Institute, Troy, NY 12181.
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.
Keywords :
Contracts; Data preprocessing; Digital images; Image processing; Maximum likelihood estimation; Parameter estimation; Probability; Stochastic processes; Systems engineering and theory; Testing; Digital image processing; maximum-likelihood estimation; texture classification;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.1982.4767197