Modeling of texture images by use of structuring elements of morphologicalfilters

We propose a new model of texture images using morphological filters. This method is based on a linear predictive model [autoregressive (AR) model], w hich is a representative texture image model. This method embeds the freque ncy characteristics of the texture image in the AR: model. In this paper, w e will demonstrate a new model that represents the spatial features of a te xture image. Morphological filters can remove the spatial features and are used for pattern spectra. In this paper, we consider embedding the spatial features in the structuring elements of morphological filters and propose a n Opening Model (OM) to model the convex up features and a Closing Model (C M) to model the convex down features. We examine the reliability of the pro posed model and present improvements to the low-reliability model. Furtherm ore, our recognition tests clearly show excellent recognition when OM and C M are used together. (C) 2001 Scripta Technica.