Modeling of semantic space is a new and challenging research topic both in cognitive science and linguistics. Existing approaches can be classified into two different types according to how the calculation are done: either a word-by-word co-occurrence matrix or a word-by-context matrix (Riordan 2007). In this paper, we argue that the existing popular distributional semantic model (vector space ...

Image splicing is a common operation in image forgery. Different techniques of image splicing detection have been utilized to regain people’s trust. This study introduces a texture enhancement technique involving the use of fractional differential masks based on the Machado entropy. The masks slide over the tampered image, and each pixel of the tampered image is convolved with the fractional ma...

Two approaches to the characterization of three-dimensional (3-D) textures are presented: one based on gradient vectors and one on generalized co-occurrence matrices. They are investigated with the help of simulated data for their behavior in the presence of noise and for various values of the parameters they depend on. They are also applied to several medical volume images characterized by the...

Image textural analysis technology has been widely used in the design of automated defect detection systems. Because the presence of defects may change the textural features of an image, a reference image without defects can be compared with the test image to detect whether there are any defects. However, besides defects, the deflection of the input test image could also change its textural fea...

The aim of the study in this research deals with the accurate texture classification and the image texture analysis has a voluminous errand prospective in real world applications. In this study, the texton co-occurrence matrix applied to the Broadatz database images that derive the template texton grid images and it undergoes to the discrete shearlet transform to decompose the image. The entrop...

In this study, a new clustering-based feature extraction algorithm is proposed for the spectral-spatial classification of hyperspectral imagery. The clustering approach is able to group the high-dimensional data into a subspace by mining the salient information and suppressing the redundant information. In this way, the relationship between neighboring pixels, which was hidden in the original d...

This work proposes a texture descriptor based on fractal theory. The method is based on the Bouligand-Minkowski descriptors. We decompose the original image recursively into 4 equal parts. In each recursion step, we estimate the average and the deviation of the Bouligand-Minkowski descriptors computed over each part. Thus, we extract entropy features from both average and deviation. The propose...

This paper addresses an estimation problem of the ball’s state of spin in RoboCup Small Size League (SSL). A spinning ball varies its speed after the ball bounces off the floor. This paper proposes an image-based estimation method of the ball’s state of spin, in particular, by using inertia feature of co-occurrence matrix of the image sequence. The effectiveness of our proposed method is shown ...

Writer identification recently has been studied and it has a wide variety of applications. Most studies are based on English documents with the assumption that the written text is fixed (text-dependent methods) and no research has been reported on Farsi or Arabic documents. In this paper, we have proposed a method for off-line writer identification based on Farsi handwriting, which is text-inde...

This study extended the computation of GLCM (gray level co-occurrence matrix) to a three-dimensional form. The objective was to treat hyperspectral image cubes as volumetric data sets and use the developed 3D GLCM computation algorithm to extract discriminant volumetric texture features for classification. As the kernel size of the moving box is the most important factor for the computation of ...