Abstract:
Texture classication is an important area in the
field of texture analysis. In this paper, we propose
a novel stochastic approach-multiresolution Markov
Random Field (MRMRF) model to represent textures
and a parameter estimation method based
on Markov chain Monte Carlo method is proposed.
The parameters estimated from the decomposed subbands
can be used as features to classify textures.
The classifier used here is nearest linear combination (NLC)
which uses the combination of the features of several
prototypes of an original texture to
fit the features of the query texture. This method
is better than NN (nearest neighbor) classifier. The
experiment results illustrate the effectiveness of our
method.