3D Mesh Evaluation Through Orthogonal Slice Perimeter Analysis
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Solution Overview
Problem
Current CAD systems face challenges in efficiently comparing and retrieving similar 3D object models due to limitations in feature extraction and similarity evaluation methods, particularly in handling variations in size and topology.
Innovation Solution
A method that processes triangular mesh data by obtaining dimensional layers from a slicer program, calculating perimeter length values in orthogonal orientations, and comparing these values to stored references to determine matching between 3D objects, allowing for scaling and topology-based similarity searches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional feature extraction methods are used for 3D object comparison, then the system can handle basic shape retrieval, but it fails to efficiently handle variations in size and topology
Solution Approach 1:
The patent segments the 3D object into multiple 2D cross-sectional slices at different heights. Each slice is processed independently to extract perimeter features, which are then aggregated to represent the entire 3D object. This segmentation approach enables the system to handle topology variations by capturing shape characteristics at multiple levels while maintaining processing efficiency through independent slice analysis.
Solution Approach 2:
The patent transforms the 3D shape comparison problem into a 2D analysis by taking cross-sectional slices at different heights. Instead of directly comparing complex 3D models, the system analyzes perimeter characteristics of 2D slices and reconstructs the 3D shape signature from these 2D measurements. This dimensional reduction simplifies the comparison process while preserving essential shape information for detecting size and topology variations.
2Measurement precision
If detailed feature analysis is performed on 3D models, then matching accuracy improves, but processing time increases significantly
Solution Approach 1:
The patent extracts only the essential perimeter length features from each 2D cross-sectional slice, discarding redundant geometric details. By focusing solely on perimeter measurements rather than analyzing complete 3D surface geometry, the system achieves sufficient matching accuracy for shape similarity detection while dramatically reducing computational complexity and processing time.
Solution Approach 2:
The patent analyzes a limited set of cross-sectional slices at strategically chosen heights rather than processing the entire 3D model surface. This partial analysis approach captures the essential shape characteristics needed for accurate matching while avoiding the computational burden of exhaustive feature extraction, thereby reducing processing time without sacrificing matching precision.
Data Source
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AI summary
A method, in each of three orthogonal orientations, obtains dimensional layers of triangular mesh data of the 3D object from a slicer program. Perimeter length values for each layer of each of the three orthogonal orientations are obtained and compared to stored perimeter length value for a reference object to determine a degree of matching. Measurement data is facilitated by processing by CNC/3D print software. Smaller objects within the 3D object are also analyzed. For a more robust approach, each triangle in the triangular mesh data is analyzed by totaling the perimeter of surrounding triangles to assign a value. Matching with the reference object is made based on the assigned total perimeter values. The 3D object can be scaled in one, two or three orthogonal dimensions to match the reference object.