How to perform texture recognition from stochastic modeling in the wavelet domain
The paper addresses content-based image retrieval from texture databases, by using stochastic modeling in the wavelet domain. It proposes an analysis of the key parameters involved in such a content-based texture retrieval. These parameters are the wavelet order and the goodness-of-fit measure used to select the best family of distributions for modeling the subband wavelet coefficients. It is shown that taking suitable parameters into consideration makes it possible to attain high retrieval rates in content-based texture retrieval.