A bstract The flavour problem of the Standard Model can be addressed through Froggatt-Nielsen (FN) mechanism. In this work, we develop an approach to study FN textures building a direct link between FN-charge assignments and measured masses mixing angles via unitary transformations in space. We specifically focus on quark sector identify most economic models able provide dynamical natural under...

In this paper, we use multiwavelet transforms to perform texture classification on twelve Brodatz textures. To increase the correct classification rate, feature selection is considered. Here we use the coevolutionary algorithm rather than the genetic algorithm (GA) which is widely used in many researches to accomplish the training phase of feature selection. In the classification phase, the mea...

A method of rotation invariant texture classification based on spatial frequency model is developed. Features are derived from the multichannel Gabor filtering method. The classification performance is first tested on a set 1440 samples of 15 Brodatz textures rotated in 12 directions (0 to 165 in steps of 15 degrees). For the 13-class problem reported in [13] we got better classification with o...

An efficient texture representation for unsupervised segmentation is addressed based on the concept of Wold decomposition. Textures are described by the wavelet tuned to various scales and rotations to describe its deterministic component, and by the autogressive model to describe its indeterministic component. The wavelet features and the AR parameters capturing the perceptual properties, "per...

endering is one of the most important tasks in computer graphics and animation , and texture maps add essential visual content to the rendered image. Unfortunately, extracting textures from a single photograph poses severe difficulties and is sometimes impossible, while artificial texture synthesis does not address the full range of desired textures. We present a method for computing high-quali...

This paper introduces a novel way that allows non-expert users to create smart surroundings. To establish this goal, we have developed a panel type smart material called “u-Texture”, which has a built-in computer and sensors. u-Textures can be connected to each other to form various furniture that support human home activities. The unique point of u-Textures is the self-organizable function, ch...

Dynamic textures are spatial-temporal processes that exhibit statistical stationarity or stochastic repetitiveness in the temporal dimension. In this paper, we study the problem of modeling and synthesizing dynamic textures using a generative version of the convolution neural network (ConvNet or CNN) that consists of multiple layers of spatial-temporal filters to capture the spatial-temporal pa...

We present a number of techniques to facilitate the generation of textures for facial modeling. In particular, we address the generation of facial skin textures from uncalibrated input photographs as well as the creation of individual textures for facial components such as eyes or teeth. Apart from an initial feature point selection for the skin texturing, all our methods work fully automatical...

Three experiments are reported concerning the texture density aftereffect. The experiments address the question of how visual texture density information is encoded by examining patterns of transfer between different textures. In the first two experiments, it is shown that manipulation of spatial frequency and orientation information does not affect the direction of the aftereffect of density (...

Three experiments are reported concerning the texture density aftereffect. The experiments address the question of how visual texture density information is encoded by examining patterns of transfer between different textures. In the first two experiments, it is shown that manipulation of spatial frequency and orientation information does not affect the direction of the aftereffect of density (...