Modeling of texture images by use of structuring elements of morphological filters.

We propose a new model of texture images using morphological filters. This method is based on a linear predictive model [autoregressive (AR) model], which is a representative texture image model. This method embeds the frequency characteristics of the texture image in the AR model. In this paper, we will demonstrate a new model that represents the spatial features of a texture 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 an Opening Model (OM) to model the convex up features and a Closing Model (CM) to model the convex down features. We examine the reliability of the proposed model and present improvements to the low-reliability model. Furthermore, our recognition tests clearly show excellent recognition when OM and CM are used together. © 2001 Scripta Technica, Electron Comm Jpn Pt 3, 84(7): 53–62, 2001 [ABSTRACT FROM AUTHOR]