Repair of Geological Models Based on Multiple Material Marching Cubes

In this paper, we present a multi-domain implicit surface reconstruction algorithm for geological modeling based on the labeling of voxel points. The improved algorithm sets a label for each voxel point to represent the type of its geological domain and then obtains all the voxel points in the void areas. After that, the improved algorithm modifies the labels of the voxel points in the void areas and finally reconstructs the geological models through the Multiple Material Marching Cubes (M3C) algorithm. The improved algorithm solves the problems of some unexpected overlaps and voids in geological modeling by setting and modifying the labels of the voxel points. Our key contribution is proposing a labeling processing method to repair the overlap and void defects generated in the geological modeling and realizing the improved M3C algorithm. The experimental results of some geological models show the performance of the improved method. Compared with the original method, the improved method can repair the overlap and void defects in geological modeling to ensure the raw structural adjacency relationships of the geological bodies.

PROCEDURAL GENERATION OF MASSIVE 3D GEOMETRY USING IMPROVED MARCHING CUBES ALGORITHM

Процедурная генерация, или создание контента во время работы программы, это сложное направление, которое требует не только понимания 3D-графики, но и навыков программирования графики, что часто сводится к изучению работы графических процессоров. Из-за такой сложности разработчики часто используют уже готовые инструменты для создания контента. Такие инструменты обобщают и упрощают работу, предоставляя большой заготовленный набор функции, который можно использовать не зная программирования вовсе. К сожалению, обобщение часто приводит к уменьшению гибкости и вводит новые ограничения. Статистика показывает, что использование процедурной генерации, для создания массивной 3D-геометрии, невозможно при использовании готовых инструментов с уже заготовленными функциями. Такие инструменты не позволяют воплотить огромные масштабы массивной геометрии в жизнь из-за различных ограничений. Кроме того, существующие алгоритмы создания 3D-геометрии часто не учитывают применение этих алгоритмов для создания массивной 3D-геометрии, например, планет. Рассматриваемый в этой работе алгоритм Marching Cubes также не учитывает применение алгоритма для создания массивной геометрии, из-за чего применение этого алгоритма в таких целях будет иметь много ограничений и много недостатков. Но данный алгоритм выбран не случайно, он обладает большой популярностью и мы поговорим почему. Данная работа фокусируется на представлении новой модификации на уже существующий алгоритм Marching Cubes в целях применения его в рамках массивной геометрии. Данный алгоритм найдет применение в компьютерных играх с космической тематикой, наш алгоритм позволяет создавать массивную 3D-геометрию планетарных масштабов даже на слабых компьютерах без особых затрат по ресурсам. Кроме того, наш алгоритм позволяет изменять сгенерированную геометрию в реальном времени, без задержек по времени, что так важно компьютерным играм. Procedural generation, or the creation of content while a program is running, is a complex area that requires not only an understanding of 3D graphics, but also graphics programming skills, which often boils down to learning how GPUs work. Because of this complexity, developers often use off-the-shelf content creation tools. Such tools generalize and simplify work by providing a large pre-built set of functions that can be used without knowing programming at all. Unfortunately, generalization often reduces flexibility and introduces new constraints. Statistics show that using procedural generation to create massive 3D geometry is impossible when using ready-made tools with already prepared functions. Such tools do not allow the huge scales of massive geometry to be brought to life due to various constraints. In addition, existing 3D geometry creation algorithms often do not account for the application of these algorithms to create massive 3D geometry such as planets. The Marching Cubes algorithm considered in this work also does not take into account the use of the algorithm for creating massive geometry, which is why the use of this algorithm for such purposes will have many limitations and many disadvantages. But this algorithm was not chosen by chance, it is very popular and we will talk why. This work focuses on modifying the existing Marching Cubes algorithm to apply it to massive geometry. This algorithm will find application in computer games with a space theme, our algorithm allows to create massive 3D geometry of planetary scales even on a low-end computers without special resource costs. In addition, our algorithm allows to change the generated geometry in real time, without time delays, which is so important for computer games.

A parallel dual marching cubes approach to quad only surface reconstruction

We present a novel method that reconstructs surfaces from volume data using a dual marching cubes approach without lookup tables. The method generates quad only meshes which are consistent across cell borders, i.e., they are manifold and watertight. Vertices are positioned exactly on the reconstructed surface almost everywhere, leading to higher accuracy than other reconstruction methods. A halfedge data structure is used for storing the meshes which is convenient for further processing. The method processes elements in parallel and therefore runs efficiently on GPU. Due to the transition between layers in volume data, meshes have numerous vertices with valence three. We use simplification patterns for eliminating quads containing these vertices wherever possible which reduces the number of elements and increases quality. We briefly describe a CUDA implementation of our method, which allows processing huge amounts of data on GPU at almost interactive time rates. Finally, we present runtime and quality results of our method on medical and synthetic data sets.

THREE-DIMENSIONAL RECONSTRUCTION BASED ON IMPROVED MARCHING CUBES ALGORITHM

Based on the standard Marching Cubes (MC) algorithm, this paper proposes an improved MC algorithm. First, the original 15 topological configurations in the MC algorithm are increased to 24, which effectively avoid the generation of voids phenomenon. To further improve the speed of three-dimensional (3D) reconstruction, in this paper, the midpoint selection method is used instead of the linear interpolation method, and the 24 configurations are divided into three types. Each class corresponds to a thread. The multi-thread parallel processing is used to improve the calculation speed. The critical region is used to realize multi-thread synchronization, and then we designed a protocol mapping table according to the idea of the message mapping table. The function pointer is triggered by macro. Processing function is called by function pointer and completes the encapsulation of the protocol mapping table, which maintains the opening and closing principle of the class and ensures the scalability of the class. Through the improved MC algorithm accuracy verification and reconstruction speed verification, it is concluded that the improved MC algorithm can make up for the voids problem. By comparing the calculation time under the two platforms of Windows and Linux, the reconstruction speed of the improved MC algorithm is approximately 30% faster than the standard MC algorithm and 40% faster than the Masala algorithm. Finally, the algorithm is applied to the medical image 3D reconstruction system, and the accuracy and applicability of the algorithm are demonstrated by two sets of examples.

Improved Algorithm to Trace Boundary Curves on Two-Dimensional Square Meshes

In the contoured cutter path computation of a mold part, the Minkowski sum shape of the mold part CAD model and an inverted cutter model is sliced by a horizontal plane at a specific height. The cutter path can be obtained by tracing the boundary curve of the cross-sectional figure in the two-dimensional (2D) square mesh model. In the boundary curve tracing of the square mesh, the 2D marching cubes method based on the classification of the cell pattern of the mesh is typically used. We extended the classification pattern so that the existence of very small shapes in the cell, which is ignored by the conventional 2D marching cubes method, is evaluated in tracing the boundary curve. By using this technology, a robust and accurate contoured cutter path can be obtained without any increase in the computation time.