A Marching Cube Algorithm Based on Edge Growth

TL;DR

This paper introduces a novel Marching Cube algorithm that improves 3D surface reconstruction by using edge growth and topological configurations, effectively reducing holes and enabling selective contour extraction.

Contribution

It proposes a new edge growth-based Marching Cube algorithm with 17 topological configurations, enhancing reconstruction accuracy and allowing selective contour extraction.

Findings

Reconstructs 3D models with fewer holes.

Performs well on main contours of models.

Extracts contours of connected parts effectively.

Abstract

Marching Cube algorithm is currently one of the most popular 3D reconstruction surface rendering algorithms. It forms cube voxels through the input image, and then uses 15 basic topological configurations to extract the iso-surfaces in the voxels. It processes each cube voxel in a traversal manner, but it does not consider the relationship between iso-surfaces in adjacent cubes. Due to ambiguity, the final reconstructed model may have holes. We propose a Marching Cube algorithm based on edge growth. The algorithm first extracts seed triangles, then grows the seed triangles and reconstructs the entire 3D model. According to the position of the growth edge, we propose 17 topological configurations with iso-surfaces. From the reconstruction results, the algorithm can reconstruct the 3D model well. When only the main contour of the 3D model needs to be organized, the algorithm performs well. In addition, when there are multiple scattered parts in the data, the algorithm can extract only the 3D contours of the parts connected to the seed by setting the region selected by the seed.