Surface Extraction Using Voxel Row End Detection
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Solution Overview
Problem
Existing surface extraction methods for three-dimensional volumes suffer from reduced accuracy due to noise, where voxels not constituting the volume are falsely detected as surface voxels, leading to incorrect extraction of object surfaces.
Innovation Solution
The method focuses on using straight-line rows as units and ignoring intermediate regions, preventing false extraction of non-object regions as object surfaces, thereby enhancing extraction accuracy by only considering end voxels in voxel rows as surface constituents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the conventional voxel-by-voxel surface extraction method is used, then the extraction process is simple to implement, but noise causes voxels not constituting the volume to be falsely detected as surface voxels, reducing extraction accuracy
Solution Approach 1:
The patent segments the three-dimensional space into straight-line rows of voxels, processing the volume along linear paths rather than examining each voxel independently. This segmentation approach maintains simplicity while improving accuracy by considering spatial continuity and context along each row, allowing the system to distinguish true surface voxels from noise-based false detections.
2Manufacturing precision
If the conventional voxel-by-voxel extraction method is used, then the processing approach is straightforward, but false detection of non-object voxels increases, reducing extraction precision
Solution Approach 1:
By segmenting the extraction process into straight-line row processing, the patent reduces the number of investigations needed per row while maintaining or improving precision. This approach processes voxels in linear sequences, allowing faster traversal through the volume compared to comprehensive voxel-by-voxel examination, thus reducing processing time without sacrificing extraction precision.
Solution Approach 2:
The patent applies partial action by focusing extraction efforts only on relevant regions along straight-line rows rather than exhaustively processing every voxel in the entire volume. This selective approach reduces unnecessary processing operations, decreasing overall processing time while maintaining extraction precision through targeted examination of potential surface regions.
Data Source
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AI summary
A surface extraction method capable of improving accuracy of extraction of surfaces of an object, a surface extraction device, and a program are proposed. A voxel space that is divided into voxels having a lattice shape, and whether or not object constituting voxels that constitute an object which is shown in the voxel space is investigated in units of voxel rows of the voxels. Ends of the continuous object constituting voxels in the voxel rows are extracted as surfaces of the object. Straight-line rows are used as units, and intermediate portions of continuous constituting regions in the straight-line rows are ignored. Thus, even when a region that does not constitute the object exists inside the object, the region that does not constitute the object can be prevented from being falsely extracted as a surface of the object without investigation of the same region two times or more.