3D Point Cloud Voxelization for Inline Metrology
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Solution Overview
Problem
Current 3D measurement methods, such as local contact measurement and commercial 3D scanning systems, are limited in their ability to provide accurate and efficient geometric measurements of 3D objects, with slow processing speeds and offline capabilities that do not meet inline productivity demands.
Innovation Solution
A computer-implemented method that voxelizes a 3D point cloud into equal-sized voxels, classifies them based on planar requirements, computes planar parameters and normal vectors, and performs edge detection to extract geometric features for posture, dimension, and shape measurements, enabling real-time 3D measurements compatible with various sensors and applications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If local contact measurement is used for mechanical parts, then measurement can be performed with simple equipment, but the processing speed is slow and full profile cannot be obtained
Solution Approach 1:
The patent segments the 3D point cloud data into multiple 2D projection planes through voxelization and projection operations. This segmentation allows parallel processing of different planes, significantly improving processing speed while maintaining measurement precision through systematic reconstruction of the complete object profile from multiple views.
Solution Approach 2:
The patent replaces traditional mechanical contact measurement systems with a computational approach using point cloud data processing. By substituting physical measurement probes with digital voxel-based analysis and projection algorithms, the system achieves both high processing speed and complete profile acquisition without mechanical constraints.
2Measurement precision
If full geometric dimension measurement by commercial 3D scanning systems is applied, then complete 3D information is provided, but the processing time is too long for inline productivity demand
Solution Approach 1:
The patent transforms the 3D measurement problem into multiple 2D projection plane problems through voxelization and projection. By working in 2D space for edge detection and feature extraction, then reconstructing 3D measurements, the system reduces computational complexity and processing time while maintaining geometric measurement accuracy suitable for inline productivity demands.
Solution Approach 2:
The patent extracts only the essential geometric features (edges, lines, planes) from the complete 3D point cloud data through selective processing of projection planes. By taking out and processing only the critical measurement information rather than analyzing every point in full 3D space, the system achieves fast processing suitable for inline applications while maintaining measurement precision.
3Reliability
If voxelization and classification of all voxels is performed, then comprehensive geometric analysis is achieved, but computational complexity increases
Solution Approach 1:
The patent applies different processing strategies to different categories of voxels based on their local characteristics. Planar voxels undergo plane fitting while non-planar voxels receive normal vector computation. This localized quality approach ensures reliable geometric feature extraction for each voxel type while reducing overall computational complexity by avoiding uniform heavy processing across all voxels.
Data Source
AI summary
Computer implemented methods and computerized apparatus for posture, dimension and shape measurements of at least one 3D object in a scanned 3D scene are provided. The method comprises receiving a point cloud and performs 3D geometric feature extraction. In one embodiment, the 3D geometric feature extraction is based on a 3D hybrid voxel-point structure, which comprises a hybrid voxel-point based normal estimation, a hybrid voxel-point based plane segmentation, a voxel-based geometric filtering, a voxel-based edge detection and a hybrid voxel-point based line extraction. Through the process of 3D geometric feature extraction, the geometric features are then passed to the geometric-based dimension and shape measurements for various applications. After 3D geometric feature extraction, a further process of feature-based object alignment is performed. According to one embodiment of the present invention, using the exact lines extracted from the 3D geometric feature extraction, the computerized apparatus generates line-to-line (L2L) pair features for each identified object in the 3D scene. The L2L pair features in turn is used for aligning the identified 3D objects with target 3D objects.