A Maximum Likelihood Approach to Texture Classification

A. L. Vickers; J. W. Modestino

doi:10.1109/TPAMI.1982.4767197

A Maximum Likelihood Approach to Texture Classification

A. L. Vickers, J. W. Modestino

Electrical & Computer Engineering

Research output: Contribution to journal › Article › peer-review

52 Scopus citations

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.

Original language	English (US)
Pages (from-to)	61-68
Number of pages	8
Journal	IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume	PAMI-4
Issue number	1
DOIs	https://doi.org/10.1109/TPAMI.1982.4767197
State	Published - Jan 1982

Keywords

Digital image processing
maximum-likelihood estimation
texture classification

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Computational Theory and Mathematics
Artificial Intelligence
Applied Mathematics

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10.1109/TPAMI.1982.4767197

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