The paper introduces the extraction of objects that are higher than their surroundings, like houses, trees, or bridges, by combining the results of a segmentation of a DTM and a texture analysis of the gray image. We propose a new algorithm (called dual rank) to extract the ground in the DTM, which can be seen as an extension of the gray opening. The extraction of trees in the gray image is don...

Texture Segmentation is a multiscale task because both the global and the local information of an image are required. The Multiscale Texture Segmentation (MTS) employs the Boltzmann probability to determine the change of state P (state) of simulated annealing. This paper presents three modifications of MTS: first, the first two items of the Maclaurin series of the Boltzmann probability is used ...

In this article a texture feature extraction scheme based on M-band wavelet packet frames is investigated. The features so extracted are used for segmentation of satellite images which usually have complex and overlapping boundaries. The underlying principle is based on the fact that different image regions exhibit different textures. Since most signifcant information of a texture often lies in...

We recently introduced an efficient technique for out-of-core rendering and management of large textured landscapes. The technique, called Batched Dynamic Adaptive Meshes (BDAM), is based on a paired tree structure: a tiled quadtree for texture data and a pair of bintrees of small triangular patches for the geometry. These small patches are TINs that are constructed and optimized off-line with ...

The exponential growth of digital image data has created a great demand for effective and efficient scheme and tools for browsing, indexing and retrieving images from a collection of large image databases. To address such a demand, this paper proposes a new content based image retrieval technique with orthogonal polynomials model. The proposed model extracts texture features that represent the ...

The process which attaches label to a digital image by understanding the contents of image is termed as Automatic Image Annotation (AIA). Color and texture are the prominent features of a digital image. The content based image understanding is possible by using the feature strength of color and texture of an image. A classifier is designed using Decision Trees (DT) and Rough Sets (RS) to tag un...

The main goal of this exploratory project was to quantify seedling density in post fire regeneration sites, with the following objectives: to evaluate the application of second order image texture (SOIT) in image segmentation, and to apply the object-based image analysis (OBIA) approach to develop a hierarchical classification. With the utilization of image texture we successfully developed a m...

In this paper we describe a new parametric model for synthesizing environmental sound textures, such as running water, rain, and fire. Sound texture analysis is cast in the framework of wavelet decomposition and multiresolution statistical models, that have previously found application in image texture analysis and synthesis. We stochastically sample from a model that exploits sparsity of wavel...

Plant diversityis essential to maintain the health of planet's ecosystems. Conservation of biodiversity is necessary for the ecological stability and productivity in natural ecosystems. The aim of this research was to study the biodiversity and richness of plant species (including trees, shrubs and grasses) related to the environmental factors (soil and physiography) in the forests of Zagros, w...

INTRODUCTION This paper describes a method for automatic analysis of the choroid in OCT images of the eye fundus in ophthalmology. The problem of vascular lesions occurs e.g. in a large population of patients having diabetes or macular degeneration. Their correct diagnosis and quantitative assessment of the treatment progress are a critical part of the eye fundus diagnosis. MATERIAL AND METHO...