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 | |
| 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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Cite this
Vickers, A. L., & Modestino, J. W. (1982). A Maximum Likelihood Approach to Texture Classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-4(1), 61-68. https://doi.org/10.1109/TPAMI.1982.4767197