Stereological techniques for solid textures

Analytical approaches, based on digitised 2D texture models, for an automatic solid (3D) texture synthesis have been recently introduced to Computer Graphics. However, these approaches cannot provide satisfactory solutions in the usual case of natural anisotropic textures (wood grain for example). Indeed, solid texture synthesis requires particular care, and sometimes external knowledge to "guess" the internal structure of solid textures because only 2D texture models are used for analysis. By making some basic assumptions about the internal structure of solid textures, we propose a very efficient method based on a hybrid analysis (spectral and histogram) for an automatic synthesis of solid textures. This new method allows us to obtain high precision solid textures (closely resembling initial models) in a large number of cases, including the difficult case of anisotropic textures.

3D solid textures are important data for computer graphics applications because they are useful for synthesizing photo realistic patterns such as stone, smoke, water, clouds, fire, and wood. Unlike typical 2D textures, 3D solid textures are represented in voxel forms, which use three-dimensional coordinates. Various kinds of research have been conducted for pattern analysis of 2D textures to help development of computer applications. However, pattern analysis of 3D solid textures has not been investigated sufficiently even though 3D data related software is emerging. In this research, we have extended higher order local autocorrelation (HLAC) 2D mask patterns to 3D mask patterns so that pattern analysis software can handle not only 2D texture images but also 3D solid textures. Our experimental system can classify and look for 3D solid textures with similar patterns from a 3D solid texture database by using 3D HLAC masks. We have examined (1) similarity retrieval of 3D solid textures and (2) pattern classification of 3D solid textures by using the system.

Compared with 2D texture method, solid texturing can achieve better realistic results. A novel solid texture synthesis method based on 2D exemplar and procedural noise is presented. First, the movement path for exemplar in 3D space is designed using procedural noise. Next, all the pixels of exemplar are used to color the 3D space through their trajectory so that the solid texture is synthesized. Experimental results show that our method is able to efficiently synthesize 3D texture to simulate the natural properties of the given 2D exemplar. The method is simple and stable, and takes on a few seconds on an ordinary PC.

In this paper, we present an improved synthesis algorithm for both 2D and solid textures. Based on the wavelet-based multi-resolution pyramids and the improved optimization of texture synthesis, a coarse texture was synthesized as a skeleton. By adding detail information to the coarse texture, the higher resolution results can be generated. This skeletal growth-like procedure makes the result more controllable. In addition, to make full use of the spatial relationships among texture pixels, wavelet coefficients rather than traditional RGB channels are used to search the nearest neighbor pixels. Experimental study shows that the method plays well for both 2D and solid texture synthesis.

We propose a novel parametric approach which aims at the synthesis of anisotropic solid textures from the analysis of a single 2D exemplar. This approach is an extension of the pyramidal scheme of Portilla and Simoncelli. It proceeds in three main steps: first, a 2D analysis of the example is performed which produces a set of reference statistics. Then, 3D reference statistics are inferred from the 2D ones thanks to specific anisotropy assumptions. The final step aims at the synthesis itself: the 3D target statistics are imposed on a random 3D block according to a specific multi resolution pyramidal scheme. The approach is applied to the synthesis of solid textures representative of the structure of dense pre-graphitic carbons. The samples are lattice fringe images obtained by high resolution transmission electronic microscopy (HRTEM). HRTEM samples with increasing structural order are used for the experimental evaluation. The produced solid textures exhibit anisotropy properties similar to those observed in the HRTEM samples. Such an approach can easily be extended to any 3D anisotropic structures showing stacks of layers such as wood grain images, seismic data, etc.

Many image acquisition techniques used in biomedical imaging, material analysis, and structural geology are capable of acquiring 3-D solid images. Computational analysis of these images is complex but necessary since it is difficult for humans to visualize and quantify their detailed 3-D content. One of the most common methods to analyze 3-D data is to characterize the volumetric texture patterns. Texture analysis generally consists of encoding the local organization of image scales and directions, which can be extremely diverse in 3-D. Current state-of-the- art techniques face many challenges when working with 3-D solid texture, where most approaches are not able to consistently characterize both scale and directional information. 3-D Riesz- wavelets can deal with both properties. One key property of Riesz filterbanks is steerability, which can be used to locally align the filters and compare textures with arbitrary (local) orientations. This paper proposes and compares three novel local alignment criteria for higher-order 3-D Riesz-wavelet transforms. The estimations of local texture orientations are based on higher- order extensions of regularized structure tensors. An experimental evaluation of the proposed methods for the classification of synthetic 3-D solid textures with alterations (such as rotations and noise) demonstrated the importance of local directional information for robust and accurate solid texture recognition. These alignment methods improved the accuracy of the unaligned Riesz descriptors up to 0.63, from 0.32 to 0.95 over 1 in the rotated data, which is better than all other techniques that are published and tested on the same database.

In the research of virtual hepatic surgery, the synthesis of hepatic texture space and the texture mapping of the hepatic body model are inseparable. Different methods for hepatic volume texture on the authenticity and mapping speed tend to have much difference. Based on computer unified device architecture (CUDA), this paper tries to present a texture synthesis and mapping method for the accelerating of hepatic body, which is used to solve the problem that traditional method under the hepatic volumetric texture synthesis and mapping process cost too much time. This new method may eliminate the traditional serial correlation of texture synthesis. What’s more, it may improve the efficiency of texture synthesis when the multithreading parallel processing for synthesis in the hepatic volumetric texture space in selecting and distributing blocks based on CUDA architecture.

Terasi constitutes an Indonesian traditional fermented product made from shrimp or fish (or a mixture of both) at a high salt concentration with or without incorporating approved additional ingredients. With a distinct flavor and solid texture (paste), terasi is widely consumed as a seasoning ingredient, but it is still produced using a traditional method that lacks quality inspection. Quality properties of terasi, i.e., physical, chemical, and microbiological aspects, are essential since they highly affect consumer acceptance. This article reviews the quality profiles of terasi, covering such aspects as food safety, health, sensory, shelf life, and its use. The safety of biological, chemical, and physical threats can be used to evaluate the quality of terasi from a safety perspective. In addition, the nutritional content, functional qualities, and satiety characteristics of terasi indicate its quality from a health standpoint. Based on taste, texture, aroma, and color, the sensory qualities of terasi are evaluated to determine its quality. From the time the product is developed until consumers utilize it without any modifications, the quality of terasi based on the shelf life aspect is observed. The quality of terasi in terms of usability is determined by items that are user-friendly or, in other words, practical

Fiat boundaries play a fundamental role in geography. Unlike bona fide boundaries which correspond to mind‐independent discontinuities in the material reality and are therefore directly accessible to the senses, fiat boundaries are immaterial and not directly accessible to the senses. Fiat boundaries are brought into existence by the acts of cognitive agents. Since they are immaterial and not directly accessible to the senses, fiat boundaries are often considered as less “real” than their bona fide counterparts. This entry discusses the distinction between bona fide and fiat boundaries and then focuses on important properties of fiat boundaries. The aim is to show that fiat boundaries are as “real” as their physical counterparts but have rather different properties. Such properties are the result of complex interrelations between cognitive agents and their environments.

Computer graphics applications often use textures to decorate virtual objects without modeling geometric details. These textures can be seamlessly generated from sample textures using texture synthesis algorithms. However, most existing texture synthesis algorithms are designed for rectangular domains and cannot be easily extended to general surfaces. In this paper, we present a novel method for texture synthesis and texture growing on triangle mesh with arbitrary topology. Using the sampled texture patches as the building blocks for texture synthesis, the visually seamless texture can be synthesized for a wide variety of textures ranging from regular to stochastic. The synthesizing process generates an initial texture block from the input texture patches and then iteratively searches for all texture blocks from the sampled texture patches to select a patch which optimizes the smoothness of the overlapping boundaries of the synthesized texture. It is showed that the proposed scheme is effective and efficient for synthesizing and growing of a wide range of textures on surfaces.

An innovative quasi-bond approach to bridge continuity, anisotropic damage and macroscopic fracture of solids and structures

Texture Mapping plays a very important role in Computer Graphics. Texture Synthesis is one of the main methods to obtain textures, it makes use of sample textures to generate new textures. Texture Transfer is based on Texture Synthesis, it renders objects with textures taken from different objects. Currently, most of Texture Synthesis and Transfer methods use a single sample texture. A method for Texture Synthesis adn Transfer from multi samples was presented. For texture synthesis, the L-shaped neighborhood seaching approach was used. Users specify the proportion of each sample, the number of seed points, and these seed points are scattered randomly according to their samples in horizontal and vertical direction synchronously to synthesize textures. The synthesized textures are very good. For texture transfer, the luminance of the target image and the sample textures are analyzed. This procedure is from coarse to fine, and can produce a visually pleasing result.

Here we present a 3‐D multi‐observable probabilistic inversion method, particularly designed for high‐resolution (regional) thermal and compositional mapping of the lithosphere and sub‐lithospheric upper mantle that circumvents the problems associated with traditional inversion methods. The key aspects of the method are as follows: (a) it exploits the increasing amount and quality of geophysical datasets; (b) it combines multiple geophysical observables (Rayleigh and Love dispersion curves, body‐wave tomography, magnetotelluric, geothermal, petrological, gravity, elevation, and geoid) with different sensitivities to deep/shallow, thermal/compositional anomalies into a single thermodynamic‐geophysical framework; (c) it uses a general probabilistic (Bayesian) formulation to appraise the data; (d) no initial model is needed; (e) compositional a priori information relies on robust statistical analyses of a large database of natural mantle samples; and (f) it provides a natural platform to estimate realistic uncertainties. In addition, the modular nature of the method/algorithm allows for incorporating or isolating specific forward operators according to available data. The strengths and limitations of the method are thoroughly explored with synthetic models. It is shown that the a posteriori probability density function (i.e., solution to the inverse problem) satisfactorily captures spatial variations in bulk composition and temperature with high resolution, as well as sharp discontinuities in these fields. Our results indicate that only temperature anomalies of ΔT ⪆150°C and large compositional anomalies of ΔMg# > 3 (or bulk ΔAl2O3 > 1.5) can be expected to be resolved simultaneously when combining high‐quality geophysical data. This resolving power is sufficient to explore some long‐standing problems regarding the nature and evolution of the lithosphere (e.g., vertical stratification of cratonic mantle, compositional versus temperature signatures in seismic velocities, etc) and offers new opportunities for joint studies of the structure of the upper mantle with unprecedented resolution.

An improved image texture synthesis based on algorithm convolution neural network

Geosphere, June 2010, v. 6, p. 237-274, doi:10.1130/GES00513.1, Plate 3 - Maps showing discretized results from three-dimensional (3D) stratigraphy model, solid volume 3D texture class model, and attribute strat_text (see text) for layers 11–16. Thin horizontal and vertical lines portray the grid cell discretization, which consists of 168 rows and 157 columns of square cells 660 ft (~198 m) on a side. The locations of drill holes that are deep enough to penetrate the upper surface of each layer, and thus serve as a point of geologic information for that layer, are shown on the stratigraphy maps. File size is 105 MB.