Gemstone Planning via 2D Image Comparison
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Solution Overview
Problem
The computational manipulation of highly-detailed, virtual 3D models of rough gemstones for determining optimal target gemstones is highly resource-intensive in terms of CPU processing time and bandwidth.
Innovation Solution
A method involving the generation of 2D images from both the rough gemstone and a 3D model of the target gemstone, with comparison of these images to determine optimal transformations such as scaling, translation, and rotation to align the target gemstone within the rough gemstone, reducing computational complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If highly-detailed virtual 3D models are used for determining optimal target gemstones, then manufacturing precision is improved, but computational resource intensity increases
Solution Approach 1:
The patent creates simplified 2D image representations (copies) of the rough gemstone from its detailed 3D model. These 2D images serve as surrogate data structures that capture essential geometric information while occupying minimal computational space. The optimization algorithm operates on these lightweight 2D copies rather than the full 3D model, dramatically reducing CPU memory requirements and processing time while preserving the accuracy needed to determine the optimal target gemstone position and orientation.
Solution Approach 2:
The patent segments the complex 3D modeling and optimization problem into distinct stages: first generating the detailed 3D model of the rough gemstone, then creating simplified 2D projection images from specific viewpoints, and finally performing optimization calculations on these 2D representations. This segmentation allows each stage to use appropriately optimized data structures - full 3D geometry where needed for accuracy, and simplified 2D images where computational efficiency is paramount.
2Manufacturing precision
If highly-detailed virtual 3D models are manipulated computationally, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent creates simplified 2D image representations (copies) of the rough gemstone from its detailed 3D model. These 2D images serve as surrogate data structures that capture essential geometric information while occupying minimal computational space. The optimization algorithm operates on these lightweight 2D copies rather than the full 3D model, dramatically reducing CPU memory requirements and processing time while preserving the accuracy needed to determine the optimal target gemstone position and orientation.
Solution Approach 2:
The patent extracts only the essential geometric information needed for optimization from the complete 3D model by generating 2D projection images from specific viewpoints. This extraction process removes unnecessary computational complexity - details such as full surface curvature data, internal inclusions, and other 3D characteristics that are not required for determining the optimal target gemstone placement. The optimization algorithm works with this extracted subset of information, simplifying the computational system while maintaining precision.
Data Source
AI summary
A method of determining an optimal target gemstone to be obtained from a rough gemstone comprises obtaining a first series of 2D images of the rough gemstone; providing a 3D model of a target gemstone to be obtained from the rough gemstone; and generating a second series of 2D images of the target gemstone from the 3D model thereof. The method then comprises comparing the first and second series of 2D images to determine an optimal transformation to be applied to the 3D model of the target gemstone.