A method for finding all images from the same category as a given query image (termed categorization) using texture features is presented. The hypothesis that two images that are similar in texture are likely to belong to the same category, is examined. A new texture feature termed N M -gram is presented. It is based on theN -gram technique that is commonly used for text similarity. The process...

Pattern is an arrangement of features which are defined by various characteristics of image such as shape, color and texture. Texture is an important characteristic for image analysis. The major trend of the research today in terms of feature extraction for classification is accuracy oriented, however usually the newer algorithms that promises better accuracy is much more complicated in its cal...

In this paper, we study texture metamorphosis, or how to generate texture samples that smoothly transform from a source texture image to a target. We propose a patternbased approach to specify the feature correspondence between two textures, based on the observation that many texture images have stochastically distributed patterns which are similar to each other. First, the user selects a patte...

OBJECTIVES The aim of the present study is to define an optimally performing computer-aided diagnosis (CAD) architecture for the classification of liver tissue from non-enhanced computed tomography (CT) images into normal liver (C1), hepatic cyst (C2), hemangioma (C3), and hepatocellular carcinoma (C4). To this end, various CAD architectures, based on texture features and ensembles of classifie...

Texture classification plays an important role in computer vision and image processing applications, which has received considerable attention over the last several decades. In this paper, diffusion approach for texture analysis based on anisotropic diffusion and local directional binary patterns (LDBP) is presented. The proposed approach uses partial differential equation (PDE) as the pre proc...

Texture remains largely underutilized in the analysis of remote sensed datasets compared to descriptors based on the orthogonal spectral dimension. This paper describes our recent efforts towards using texture to automate the annotation of remote sensed imagery Two applications are described that use the homogeneous texture descriptor recently standardized by MPEG-7. In the Jirst, higher-level ...

This paper presents a novel approach for visual scene representation, combining the use of quantized color and texture local invariant features (referred to here as visterms) computed over interest point regions. In particular we investigate the different ways to fuse together local information from texture and color in order to provide a better visterm representation. We develop and test our m...

Texture is an important spatial feature, useful for segmenting objects in an image. Texture Spectrum is a statistical approach to texture analysis. In this paper we proposed a Texture-based approach that considers the vagueness of the images and has into account the human beings.

This paper presents a survey on the various techniques used for color and statistical texture feature extraction. The paper also discusses the use of color co occurrence matrices for feature extraction which is used for detection of plant diseases. The techniques for statistical texture analysis and color feature extraction discussed in the paper are reviewed on the basis of available literatur...

Texture analysis and classification remain as one of the biggest challenges for the field of computer vision and pattern recognition. On this matter, Gabor wavelets has proven to be a useful technique to characterize distinctive texture patterns. However, most of the approaches used to extract descriptors of the Gabor magnitude space usually fail in representing adequately the richness of detai...