A scale-elastic discrete grid structure for voxel-based modeling and management of 3D data

https://doi.org/10.1016/j.jag.2022.103009Get rights and content
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Highlights

  • A scale-elastic grid structure (SEGS) for 3D discrete grid systems is proposed.

  • The SEGS satisfies the anisotropic scale requirements of voxels in three dimensions.

  • Voxel-based modeling and management are fundamental for processing 3D voxel data.

  • SEGS method can effectively compress the voxel model while retaining accuracy.

  • SEGS method can greatly improve the efficiencies of indexing and querying voxel data.

Abstract

Three-dimensional (3D) discrete grid systems have been widely applied to voxel-based modeling and the management of 3D data. In the existing rigid grid structure (RGS), the scales of the RGS-based voxel grid in X/Y/Z dimensions are interrelated. Therefore, the RGS cannot satisfy the anisotropic scale requirements of voxels in different dimensions, rendering RGS-based methods unable to compress the voxel model effectively and manage voxels efficiently. A scale-elastic grid structure (SEGS) was proposed to solve these problems and applied to voxel-based modeling and management. Comparisons with the RGS showed that when the voxel model accuracy remained unchanged, the storage space of the voxel model generated by the SEGS-based method decreased to 12.9% on average, whereas the efficiency of decoding the voxel model increased by 3.34 times on average. The efficiencies of importing, indexing, and querying voxel data by the SEGS-based method increased by 5.27, 6.84, and 3.19 times on average.

Keywords

Discrete grid system
Scale-elastic grid structure
Voxel-based modeling
Voxel model compression
Voxel data management

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These authors contributed equally to the work and are co-first authors.