Solid texture synthesis based on 2D exemplar and procedural noise

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.

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.

Synthesizing solid particle textures via a visual hull algorithm

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.

We describe the use of traditional stereological methods to synthesize 3D solid textures from 2D images of existing materials. We first illustrate our approach for aggregate materials of spherical particles, and then extend the technique to apply to particles of arbitrary shapes. We demonstrate the effectiveness of the approach with side-by-side comparisons of a real material and a synthetic model with its appearance parameters derived from its physical counterpart. Unlike ad hoc methods for texture synthesis, stereology provides a disciplined, systematic basis for predicting material structure with well-defined assumptions.

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.

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.

We present the Mokume dataset for solid wood texturing consisting of 190 cube-shaped samples of various hard and softwood species documented by high-resolution exterior photographs, annual ring annotations, and volumetric computed tomography (CT) scans. A subset of samples further includes photographs along slanted cuts through the cube for validation purposes. Using this dataset, we propose a three-stage inverse modeling pipeline to infer solid wood textures using only exterior photographs. Our method begins by evaluating a neural model to localize year rings on the cube face photographs. We then extend these exterior 2D observations into a globally consistent 3D representation by optimizing a procedural growth field using a novel iso-contour loss. Finally, we synthesize a detailed volumetric color texture from the growth field. For this last step, we propose two methods with different efficiency and quality characteristics: a fast inverse procedural texture method, and a neural cellular automaton (NCA). We demonstrate the synergy between the Mokume dataset and the proposed algorithms through comprehensive comparisons with unseen captured data. We also present experiments demonstrating the efficiency of our pipeline's components against ablations and baselines. Our code, the dataset, and reconstructions are available via https://mokumeproject.github.io/.

Implementation of manifold coverage for 3D rock fracture network modeling and its application in rock permeability prediction

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.

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.

An improved image texture synthesis based on algorithm convolution neural network

<p>This paper presents a 3D guidance scheme for<br>\nUnmanned Aerial Vehicles (UAVs). The proposed guidance scheme<br>\nis based on the sliding mode approach using nonlinear sliding<br>\nmanifolds. Generalized 3D kinematic equations are considered<br>\nhere during the design process to cater for the coupling between<br>\nlongitudinal and lateral motions. Sliding mode based guidance<br>\nscheme is then derived for the multiple-input multiple-output<br>\n(MIMO) system using the proposed nonlinear manifolds. Instead of<br>\ntraditional sliding surfaces, nonlinear sliding surfaces are proposed<br>\nhere for performance and stability in all flight conditions. In the<br>\nreaching phase control inputs, the bang-bang terms with signum<br>\nfunctions are accompanied with proportional terms in order to reduce<br>\nthe chattering amplitudes. The Proposed 3D guidance scheme is<br>\nimplemented on a 6-degrees-of-freedom (6-dof) simulation of a UAV<br>\nand simulation results are presented here for different 3D trajectories<br>\nwith and without disturbances.</p>

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.

Research on medical applications of contrast sensitivity function to red–green gratings in 3D space