Texture Characterization and Texture-Based Image Partitioning Using Two-Dimensional Linear Estimation Techniques

Abstract

A new approach to texture characterization and texture-based image partitioning is presented. In this approach the gray level of each pixel of an image is estimated from a weighted sum of gray levels of its neighbor pixels. The weight coefficients are determined so that the mean square estimation error is minimized. The obtained two-dimensional estimator characterizes the texture of the sample and can be used to discriminate other classes of textures. This texture characterization technique is applied to image partitioning, and two partitioning procedures are developed. Experimental results obtained by their application are also shown.