Modification of the Marching Cubes Algorithm to Obtain a 3D Representation of a Planar Image

2021 ◽  
Vol 47 (3) ◽  
pp. 215-223
Author(s):  
Delia Irazú Hernández Farías ◽  
Rafael Guzmán Cabrera ◽  
Teodoro Cordova Fraga ◽  
José Zacarías Huamaní Luna ◽  
Jose Francisco Gomez Aguilar
2020 ◽  
Vol 32 (5) ◽  
pp. 167-180
Author(s):  
Delia Irazu Hernández Farías ◽  
Rafael Guzmán Cabrera ◽  
Teodoro Cordova Fraga ◽  
Jose Zacarías Huamaní Luna ◽  
Jose Francisco Gomez Aguilar

The registration of a 3D model over an image can be seen as the alignment of visual correspondences extracted from these two data. This is a challenging task and it is even more complex when the two images have a different modality. This paper introduces an approach that allows matching features detected in two different modalities: photographs and 3D models, by using a common 2D representation. Our approach is based on a modifcation of the Marching Cubes algorithm aiming to remove ambiguous cases without adding further calculations in each cube. We share the idea about the crucial importance of splitting the equivalence cases into two classes. Considering all the possible states inside/outside in the four corners of a cube side, indeed, there are only four non-trivial cases after eliminating those equivalences through the rotation. The obtained results allow us to validate the feasibility of the proposed methodology.


2005 ◽  
Vol 5 (2) ◽  
pp. 111-115 ◽  
Author(s):  
Tomoyuki Fujimori ◽  
Hiromasa Suzuki ◽  
Yohei Kobayashi ◽  
Kiwamu Kase

This paper describes a new algorithm for contouring a medial surface from CT (computed tomography) data of a thin-plate structure. Thin-plate structures are common in mechanical structures, such as car body shells. When designing thin-plate structures in CAD (computer-aided design) and CAE (computer-aided engineering) systems, their shapes are usually represented as surface models associated with their thickness values. In this research, we are aiming at extracting medial surface models of thin-plate structures from their CT data for use in CAD and CAE systems. Commonly used isosurfacing methods, such as marching cubes, are not applicable to contour the medial surface. Therefore, we first extract medial cells (cubes comprising eight neighboring voxels) from the CT data using a skeletonization method to apply the marching cubes algorithm for extracting the medial surface. It is not, however, guaranteed that the marching cubes algorithm can contour those medial cells (in short, not “marching cubeable”). In this study, therefore we developed cell operations that correct topological connectivity to guarantee such marching cubeability. We then use this method to assign virtual signs to the voxels to apply the marching cubes algorithm to generate triangular meshes of a medial surface and map the thicknesses of thin-plate structures to the triangle meshes as textures. A prototype system was developed to verify some experimental results.


2020 ◽  
Vol 40 (2) ◽  
pp. 8-15 ◽  
Author(s):  
William E. Lorensen ◽  
Chris Johnson ◽  
Dave Kasik ◽  
Mary C. Whitton

2011 ◽  
Vol 110-116 ◽  
pp. 4832-4836
Author(s):  
Yao Tien Chen

We propose an approach, integrating Bayesian level set method with modified marching cubes algorithm for brain tissue and tumor segmentation and surface reconstruction. First, we extend the level set method based on the Bayesian risk to three-dimensional segmentation. Then, the three-dimensional Bayesian level set method is used to segment solid three-dimensional targets (e.g., tissue, whole brain, or tumor) from serial slice of medical images. Finally, the modified marching cubes algorithm is used to continuously reconstruct the surface of targets. Since each step can definitely obtain an appropriate treatment by statistical tests, the tissue and tumor segmentation and surface reconstruction are expected to be satisfied.


Author(s):  
А.А. Третьяков

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.


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