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 language | English (US) |
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Pages (from-to) | 79-84 |
Number of pages | 6 |
Journal | Proceedings of the IEEE Conference on Decision and Control |
Volume | 1 |
DOIs | |
State | Published - Jan 1 1979 |
Event | Proc IEEE Conf Decis Control Incl Symp Adapt Processes 18th - Fort Lauderdale, FL, USA Duration: Dec 12 1979 → Dec 14 1979 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Modeling and Simulation
- Control and Optimization