3D Shape Identification Using Multi-Axis Image Alignment
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Solution Overview
Problem
Existing 3D shape design processes face challenges in accurately classifying and standardizing past datasets due to improper classifications and numerous similar shapes, leading to increased man-hours and difficulty in deriving dimensional relationships among parts.
Innovation Solution
A method involving the generation of normalized unit shape datasets by aligning orientations based on parametric relationships, using 2D images captured from multiple axes to identify corresponding portions and derive dimensional relationships among parts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional classification methods are used for past 3D shape datasets, then the design process can proceed, but the classification accuracy deteriorates due to improper classifications and numerous similar shapes
Solution Approach 1:
The patent segments the classification process into multiple stages: first generating unit shape datasets by dividing 3D shapes into standardized units, then comparing these units to identify corresponding portions. This segmentation transforms a complex overall classification task into manageable sequential steps, improving classification accuracy without overwhelming system complexity
Solution Approach 2:
The patent creates standardized unit shape datasets that serve as simplified copies or representations of the original 3D shapes. By working with these standardized unit representations rather than complex original geometries, the system achieves accurate classification while reducing computational complexity
2Productivity
If manual design processes are used for 3D shape design, then design flexibility is maintained, but productivity deteriorates due to large number of man-hours required
Solution Approach 1:
The patent enables the system to automatically perform classification and identification tasks that previously required manual intervention. By implementing automated comparison of unit shape datasets and automatic identification of corresponding portions, the system serves itself in the classification process, dramatically improving productivity while reducing time loss
Solution Approach 2:
The patent transforms 3D shape data into standardized unit parameters that can be systematically compared and processed. By changing the representation from complex 3D geometries to standardized unit parameters, the system enables efficient automated processing while maintaining design flexibility
3Measurement precision
If orientation alignment is not performed, then processing speed is maintained, but measurement precision deteriorates in identifying corresponding portions between shape datasets
Solution Approach 1:
The patent performs orientation alignment as a preliminary step before comparing unit shape datasets. By pre-aligning the orientations of the shape datasets, the system ensures accurate identification of corresponding portions without requiring complex real-time adjustment mechanisms during comparison
Data Source
AI summary
A shape identification program causes a computer to execute a process including acquiring a third shape dataset and a fourth shape dataset, respectively generated by changing sizes of a first shape dataset and a second shape dataset in each of directions of a plurality of coordinate axes according to a specific rule, and generating a first plurality of images and a second plurality of images by capturing the third shape dataset and the fourth shape dataset, respectively, from both directions of the respective plurality of coordinate axes. The process further includes identifying a second portion in the second shape dataset corresponding to a first portion in the first shape dataset by aligning orientations of the first shape dataset and the second shape dataset based on a result of comparison between the first plurality of images and the second plurality of images.