Gem Pattern Matching Algorithm for Gemstone Identification
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Solution Overview
Problem
Current methods lack an efficient algorithm to compare a gemstone's refraction pattern to a database of known patterns to determine a percentage match, which is essential for gemstone identification and authentication.
Innovation Solution
A method that analyzes a gemstone's refracted digital pattern by comparing the area and clockwise angle of the largest spots in 96 concentric bands to a database of pre-processed derivative information, using a two-phase matching process to calculate a percentage match, involving normalization and rotation of the patterns to align with the database entries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a refraction pattern is obtained from a specific gemstone and compared to a database of refraction patterns of known gemstones, then gemstone identification and authentication can be performed, but no efficient algorithm exists to determine a percentage match between the target gemstone and database patterns
Solution Approach 1:
The refraction pattern is divided into 96 concentric circular bands, and within each band, multiple spots are identified and characterized by their area and clockwise angle. This segmentation transforms the complex continuous pattern into discrete, comparable units, enabling efficient percentage match calculation while maintaining measurement precision.
2Reliability
If the entire gemstone digital pattern is stored in the database for comparison, then complete pattern matching can be performed, but storage requirements and processing time increase significantly
Solution Approach 1:
Instead of storing and comparing entire 512x512 pixel patterns, the algorithm extracts only the critical features: the area and clockwise angle of the largest spot in each of the 96 concentric bands. This extraction reduces data volume dramatically while preserving the essential characteristics needed for accurate gemstone identification and authentication.
Solution Approach 2:
The database patterns are pre-processed into derivative information containing normalized spot areas and angles for all 96 concentric bands. This preliminary transformation allows rapid comparison with target gemstones without requiring full pattern processing during authentication, significantly reducing processing time while maintaining reliability.
3Measurement precision
If the gemstone pattern is normalized and rotated to align with database entries, then matching accuracy improves, but additional processing steps are required
Solution Approach 1:
The algorithm applies normalization and rotation transformations to align the target gemstone pattern with database entries. By changing the orientation and scale parameters of the pattern, the system achieves accurate matching even when gems are positioned or oriented differently during imaging, improving measurement precision through systematic parameter adjustment.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables efficient storage and verification of gemstones by determining a high percentage match between a target gemstone and known gemstones in the database, facilitating authentication and identification with a high degree of accuracy.
Implementation Method 1
transmitting a beam of light such as from a laser beam into a gemstone and recording the refraction pattern emitted by the gemstone
Data Source
AI summary
A method and gem pattern matching technique to analyze a target gemstone by analyzing a pattern created by transmitting a light source such as a laser beam through the gemstone to create a visual optical pattern and comparing the pattern to a database of known gemstone patterns to determine the percentage likelihood that the target gemstone will match a gemstone in the database. The matching is based on the weight of the heaviest spot in the pattern and its location in the gemstone image and comparing it to the weight and location of the heaviest spots in each gemstone image in the database to determine a percentage matching.