In this paper, texture analysis based on wavelet transformations is elaborated. The paper is meant as a practical guideline through some aspects of a wavelet-based texture analysis task. The following aspects of the problem are discussed: discrete and continuous wavelet decompositions, texture features for grey-level textures, extensions to colour texture and rotation-invariant features, and cl...

introduction: the process of discriminating among benign and malignant hyperplasia begun with subjective methods using light microscopy and is now being continued with computerized morphometrical analysis requiring some features. one of the main features called volume percentage of stroma (vps) is obtained by calculating the percentage of stroma texture. currently, this feature is calculated by...

| This report gives an introduction to the application of wavelet based multiscale image analysis methods to texture analysis. It outlines the basic methods and comments on design issues. It also points to the literature and connections with related methods. The unnnishedness of the research in this area becomes clear from the discussion of some extra issues and from a short list of practical a...

This paper describes the state of the art in segmentation algorithms of aerial images. Different approaches and object classes are described and their advantages and limitations are shown. First the advantage of multiple input data (e.g., color, infrared, DEM) and the information that can be derived from these sources is discussed. Besides sensor data, “synthetic” input images (e.g., using text...

We take a look at texture analysis research over the past 25 years, from the persective of the Human Vision and Electronic Imaging conference. We consider advances in the understanding of human perception of textures and the development of texture analysis algorithms for practical applications. We cover perceptual models and algorithms for image halftoning, texture discrimination, texture segme...

Texture is a surface property which is used to identify and recognize the object. Texture analysis is important in many applications of computer image analysis for classification and segmentation of images based on local spatial patterns of intensity or color. In texture classification the goal is to assign an unknown sample image to one set of known texture classes. The proposed method is text...

This chapter aims to provide an overview of the foundations of texture processing for biomedical image analysis. Its purpose is to define precisely what biomedical texture is, how is it different from general texture information considered in computer vision, and what is the general problem formulation to translate 2D and 3D textured patterns from biomedical images to visually and biologically ...

Texture is a surface property which is used to identify and recognize the object. Texture analysis is important in many applications of computer image analysis for classification and segmentation of images based on local spatial patterns of intensity or color. In texture classification the goal is to assign an unknown sample image to one set of known texture classes. The proposed method is text...

Optimal texture analysis algorithms for describing degradation of carpets are identified. Experimental design is applied to select from a set of texture analysis algorithms those optimal for identifying texture changes due to degradation of carpets. The degree of wear of a degraded carpet is quantified by comparing its texture to the original texture. The set of texture algorithms is applied on...