Texture Discrimination Based Upon an Assumed Stochastic Texture Model

James W. Modestino; Acie L. Vickers; Robert W. Friles

doi:10.1109/TPAMI.1981.4767148

Texture Discrimination Based Upon an Assumed Stochastic Texture Model

James W. Modestino, Acie L. Vickers, Robert W. Friles

Electrical & Computer Engineering

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

31 Scopus citations

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)
Pages (from-to)	557-580
Number of pages	24
Journal	IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume	PAMI-3
Issue number	5
DOIs	https://doi.org/10.1109/TPAMI.1981.4767148
State	Published - Sep 1981

Keywords

Digital filtering
image processing
random fields
texture discrimination

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.1981.4767148

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