M-BAND WAVELETS: APPLICATION TO TEXTURE SEGMENTATION FOR REAL LIFE IMAGE ANALYSIS

Abstract

This paper describes two examples of real-life applications of texture segmentation using M-band wavelets. In the first part of the paper, an efficient and computationally fast method for segmenting text and graphics part of a document image based on textural cues is presented. It is logical to assume that the graphics part has different textural properties than the non-graphics (text) part. So, this is basically a two-class texture segmentation problem. The second part of the paper describes a segmentation scheme for another real-life data such as remotely sensed image. Different quasi-homogeneous regions in the image can be treated to have different texture properties. Based on this assumption the multi-class texture segmentation scheme is applied for this purpose.