Mark Edge Frequency Profiling for Counterfeit Detection
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Solution Overview
Problem
Existing anti-counterfeiting technologies require additional equipment and materials, adding complexity to the production process and are often difficult to distinguish genuine marks from counterfeit ones.
Innovation Solution
A computing device analyzes images of candidate marks by measuring edge characteristics, creating filtered profiles using band-pass filters for specific spatial frequency bands, and comparing these profiles with genuine mark profiles to determine authenticity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If additional equipment and materials are used for anti-counterfeiting codes, patterns, and indicia, then the ability to distinguish genuine marks from counterfeits is improved, but the device complexity and manufacturing process complexity increase
Solution Approach 1:
The patent uses optical copying through image capture devices to create digital representations of marks. The system captures images of both genuine and candidate marks, then processes these digital copies through algorithms that analyze edge characteristics and spatial frequency components. This allows authentication without requiring complex physical anti-counterfeiting features or additional manufacturing equipment.
Solution Approach 2:
The patent replaces traditional mechanical anti-counterfeiting measures (physical codes, patterns, microfibers, microdots) with an optical-digital system. Instead of relying on complex physical indicia that require special manufacturing equipment, the system uses image capture devices combined with computational algorithms to analyze mark characteristics, substituting mechanical complexity with optical and computational methods.
2Reliability
If traditional anti-counterfeiting codes and indicia are inserted into products, then authentication capability is improved, but the ease of manufacture deteriorates
Solution Approach 1:
The system creates digital copies of marks through image capture and processes these copies algorithmically. This allows authentication functionality to be added through software processing rather than physical modifications to the manufacturing process, maintaining ease of manufacture while improving authentication capability.
Solution Approach 2:
The patent introduces an intermediary computational layer between the physical mark and the authentication decision. Image capture devices serve as intermediaries to convert physical marks into digital data, which then undergoes processing through algorithms that analyze edge characteristics and spatial frequency components. This intermediary digital processing layer enables authentication without complicating the physical manufacturing process.
3Measurement precision
If multiple spatial frequency bands are analyzed for authentication, then the measurement precision of mark characteristics is improved, but the processing time increases
Solution Approach 1:
The patent segments the spatial frequency analysis into distinct bands (first spatial frequency band and second spatial frequency band). By dividing the frequency spectrum into separate segments and analyzing each independently through dedicated filtering operations, the system achieves precise measurement of different mark characteristics while managing processing complexity through structured division of the analysis task.
Solution Approach 2:
The system applies partial action by selecting specific spatial frequency bands for analysis rather than processing the entire frequency spectrum. The first and second spatial frequency bands are chosen to capture the most discriminative characteristics for authentication, providing sufficient measurement precision without the excessive processing time that would result from analyzing all frequency components.
Data Source
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AI summary
A method on a computing device, for determining whether a mark is genuine, the method comprising: - receiving an image of a candidate mark, and measuring a characteristic of an edge of the candidate mark, resulting in a set of measurements, and creating a profile for the feature based on the measurements; - creating a first filtered profile for the edge by filtering, from the profile of the edge, all spatial frequency components except for those in a first spatial frequency band; - creating a second filtered profile by filtering all spatial frequency components except for those in a second spatial frequency band; - comparing the first filtered profile of the edge with an equivalent first filtered profile of an edge of a genuine mark; - comparing the second filtered profile of the edge with an equivalent second filtered profile of an edge of the genuine mark; - determining whether the candidate mark is genuine based on the first filtered profile comparison and the second filtered profile comparison.