In this work, we introduce a new fusion framework for multispectral face recognition in the textures space. Active and passive infrared imaging modalities are used and comparison with visible face recognition is performed. The proposed texture space is based on the use of LBP (Local Binary Pattern) and LTP (Local Ternary Pattern) techniques. Also, a new adaptive texture descriptor is presented....

In this work, a heterogeneity feature, calculable from SAR images on a per-pixel basis, but relying on global image statistics, is described and discussed. Starting from the multiplicative speckle and texture models relating the amount of texture and speckle to the local mean and variance at every pixel, such a feature is rigorously derived from Shannon’s information theory as the conditional i...

We propose a new method of texture analysis and classification based on a local center-symmetric covariance analysis, using Kullback (log-likelihood) discrimination of sample and prototype distributions. Features of our analysis are generalized, invariant, local measures of texture having centersymmetric patterns, which is characteristic of many natural and artificial textures. We introduce two...

We explored the contribution to perception of orientation-modulated textures of visual processes selective either for orientation contrast or orientation grouping. To distinguish between these two processes we manipulated the axis of local grouping of texture elements independently of the direction of global orientation modulation. The general question posed was whether visibility of texture st...

OBJECTIVE This paper focuses on the use of image-based machine learning techniques in medical image analysis. In particular, we present some variants of local binary patterns (LBP), which are widely considered the state of the art among texture descriptors. After we provide a detailed review of the literature about existing LBP variants and discuss the most salient approaches, along with their ...

The problem of visual speech representation for bimodal based speech recognition includes particular challenges in the modeling of the inner lip texture reflecting different pronunciations, such as the appearance of teeth and tongue. This paper proposes and analyzes several possible statistical inner lip texture descriptors to determine an effective and discriminant feature. Simply using graysc...

Level-of-detail modeling is a vital representation for real-time applications. To support texture mapping progressive meshes (PM), we usually allow the whole PM sequence to share a common texture map. Although such a common texture map can be derived by using appropriate mesh parameterizations that consider the minimization of geometry stretch, texture stretch, or even the texture deviation int...

An AM30 magnesium alloy was processed through ECAP method at 200 °C. Optical and transmission electron microscopy as well as electron back scattered diffraction (EBSD) technique were employed to characterize the deformed microstructure. A partially recrystallized microstructure including ultrafine/nano structures was obtained. The area fraction of 49% was measured for the recrystallized regions...

The problem of scale in shape from texture is addressed. The need for (at least) two scale parameters is emphasized; a local scale describing the amount of smoothing used for suppressing noise and irrelevant details when computing primitive texture descriptors from image data, and an integration scale describing the size of the region in space over which the statistics of the local descriptors ...

This chapter clarifies the important aspects of biomedical texture analysis under the general framework introduced in Chapter 1. It was proposed that any approach can be characterized as the combination of local texture operators and regional aggregation functions. The type of scale and directional information that can or cannot be modeled by categories of texture processing methods is revealed...