This paper proposes a novel method for texture classification using high-order local pattern descriptor: Local Derivative Pattern (LDP). LDP is used to encode directional pattern features based on local derivative variations. The nth order LDP is proposed to encode the (n-1)th order local derivative direction variations, which can capture more detailed information. The local texture information...

In this paper, logical operators are used for analyzing texture properties and an algorithm is presented for texture image classification. Operators constructed from logical building blocks are convolved with texture images. An optimal set of six operators are selected based on their texture discrimination ability. The responses are then converted to standard deviation matrices computed over a ...

Meningioma subtype classification is a complex pattern classification problem of digital pathology due to heterogeneity issues of tumor texture, low inter-class and high intra-class texture variations of tumor samples, and architectural variations of cellular components. The basic aim is the achievement of significantly high classification results for all the subtypes of meningioma while dealin...

in this paper, the performance of 11 different distances for image retrieval and classification, based on color, shape and texture, is evaluated. the precision-recall measure and the correct classification rate of the k-nn classifier are used to evaluate retrieval and classification performances, respectively. the experimental results for a database of 1000 images from 10 different semantic gro...

Texture is often considered as a repetitive pattern and the constructing structure is known as texel. The granularity of a texture, i.e. the size of a texel, is different from one texture to another and hence inspiring us applying scale space techniques to texture classification. In this paper Gaussian kernels with different variances (s ) are convolved with the textures from Brodatz album to g...

Texture is an important spatial feature, useful for identifying objects or regions of interest in an image. One of the most popular statistical methods used to measure the textural information of images is the grey-level co-occurrence matrix (GLCM). The other statistical approach to texture analysis is the texture spectrum approach. The present paper combines the fuzzy texture unit and GLCM app...

This paper describes the usage of geoetic algorithms as feature selectors in a texture classification system. This is part of a system developed within a research project concerning the classification of genuine texture. An attempt is made to underline why an automised feature selector is a useful part of the texture classification system. Furthermore the way of including the genetic algorithms...

This paper describes the usage of geoetic algorithms as feature selectors in a texture classification system. This is part of a system developed within a research project concerning the classification of genuine texture. An attempt is made to underline why an automised feature selector is a useful part of the texture classification system. Furthermore the way of including the genetic algorithms...

Texture classification, especially color texture classification, is considered a significant step in segmentation and object classification. The property of color and texture is important for characterizing objects in natural scenes. Fractal dimension (FD) has many applications in the field of image compression and image segmentation. A series of FD features, such as mean, standard deviation, l...