Texture synthesis techniques require nearly uniform texture samples, however identifying suitable texture samples in an image requires significant data preprocessing. To eliminate this work, we introduce a fully automatic pipeline to detect dominant texture samples based on a manifold generated using the diffusion distance. We define the characteristics of dominant texture and three different t...

As digital images become more widely used, digital image analysis must find more tools to work on them. Texture analysis is a huge challenge nowadays, since simple images may be considered as a mosaic of textures separated by some boundaries. That is why both texture retrieval and classification, combined with image segmentation, may be very powerful in image analysis. Texture retrieval (ie. to...

The general problem of unsupervised textured image segmentation remains a fundamental but not entirely solved issue in image analysis. Many studies have proven that statistical model-based texture segmentation algorithms yield good results provided that the model parameters and the number of regions be known a priori. In this paper, we present an unsupervised texture segmentation method which d...

This paper studies the applicability of ERS-1 and JERS SAR-images to land-use classification. Different factors affecting classification accuracy like environmental conditions of study area, speckle filtering, spatial averaging, texture measures and different ways to use temporal images are discussed. Classification experiment employing three principal component images computed from median filt...

In this paper we present our ongoing work for getting the discrimination power of the Fuzzy Texture Spectrum encoding. The model we propose provides the classes encoded by the spectrum having outstanding power for getting homogeneous, granulated and structured texture image characterization. Moreover, we provide the membership functions allowing getting the degrees to which an image (or image p...

Abstract Before planning the use of existing land resources for irrigation, it is necessary to determine their availability. The primary goal this research was examine Guder watershed's resource potential irrigation development and create a geo-referenced map these using geographic information system coupled with fuzzy logic. Irrigation suitability criteria such as slope, use, proximity water b...

submitted for the degree of Doctor of Philosophy Trinity Term 2004 This thesis investigates the problem of classifying textures from their imaged appearance without imposing any constraints on, or requiring any a priori knowledge of, the viewing or illumination conditions under which the images were obtained. Weak classification algorithms based on the statistical distribution of texton primiti...

Texture is an important visual attribute used to describe the pixel organization in an image. As well as it being easily identified by humans, its analysis process demands a high level of sophistication and computer complexity. This paper presents a novel approach for texture analysis, based on analyzing the complexity of the surface generated from a texture, in order to describe and characteri...

Purpose: To assess whether automated texture analysis of CT images enables discrimination among pathologic classes of lung adenocarcinomas, and thus serves as an in vivo biomarker of lung cancer prognosis. Materials and Methods: Chest CTs of 30 nodules in 30 patients with resected adenocarcinomas were evaluated by a pulmonary pathologist who classified each resected cancer according to the Inte...

The problem of textured image segmentation upon an unsupervised scheme is addressed. In the past two decades, there has been much interest in segmenting images involving complex random or structural texture patterns. However, most unsupervised segmentation techniques generally suffer from the lack of information about the correct number of texture classes. Therefore, this number is often assume...