Texture analysis describes a variety of image analysis techniques that quantify the variation
in intensity and pattern. This paper provides an overview of several texture analysis …

Texture analysis is used in a very broad range of fields and applications, from texture
classification (eg, for remote sensing) to segmentation (eg, in biomedical imaging), passing …

Abstract Local Binary Patterns (LBP) have emerged as one of the most prominent and
widely studied local texture descriptors. Truly a large number of LBP variants has been …

Local binary patterns (LBP) achieve great success in texture analysis, however they are not
robust to noise. The two reasons for such disadvantage of LBP schemes are (1) they encode …

Motivated by researching new image texture modeling that improves state-of-the-art LBP
variants and non-LBP descriptors, this paper proposes a novel approach for constructing …

In the aerospace industry, automated fibre laying processes are often applied for
economical composite part fabrication. Unfortunately, the current mandatory visual quality …

This paper presents a novel voxel-based method for texture analysis of brain images.
Texture analysis is a powerful quantitative approach for analyzing voxel intensities and their …

This paper proposes a method for color-texture analysis by learning spatio-spectral
representations from a complex network framework using the Randomized Neural Network …

Stability of radiomic features in CT perfusion maps - IOPscience Skip to content IOP Science
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Moment invariants are important shape descriptors in computer vision. In this study, we
propose new sets of quaternion moment descriptors for color image. They are constructed in …