Surface Microstructure Identification via Optical Imaging
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Solution Overview
Problem
Current methods for counterfeiting, tampering, and traceability in materials or documents rely heavily on visible markings or complex encoding, which are not effective for mass-serialization applications, particularly in industries where aesthetic or mechanical constraints prevent visible markings.
Innovation Solution
The use of optical imaging to capture and analyze the unique microstructure of a product's surface, allowing for reliable and fast identification without any physical markings, by digitizing and cross-correlating images to identify products uniquely based on their microscopic features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visible markings or complex encoding are used for identification, then security against counterfeiting and tampering is improved, but the aesthetic appearance and mechanical properties of the material are compromised
Solution Approach 1:
The patent extracts the identification function from visible markings and transfers it to the invisible microstructure of the material surface. The unique natural pattern of the material itself serves as the identifier, eliminating the need for separate visible security features that would compromise aesthetics.
Solution Approach 2:
The patent creates a digital copy of the unique microstructural pattern through optical imaging and uses this digital replica for identification purposes. This allows the physical material to remain unmarked while its digital twin provides security verification.
2Loss of information
If visible markings are applied for traceability, then product tracking capability is improved, but the mechanical integrity and surface quality are degraded
Solution Approach 1:
The patent removes the need for surface markings by extracting and utilizing the inherent unique microstructural characteristics of the material. The natural variations in the material's microstructure serve as the traceability identifier, preserving surface quality.
Solution Approach 2:
The material's own microstructure serves as the identification medium. The unique natural pattern inherent in each material piece provides traceability without requiring external markings or modifications.
3Productivity
If traditional marking methods are used for mass-serialization, then identification speed is improved, but the complexity of the system and cost increase
Solution Approach 1:
The patent replaces mechanical marking systems with optical imaging and digital pattern recognition. Instead of physically marking each item, the system captures optical images of the microstructure and uses automated image processing for identification, significantly reducing system complexity.
Solution Approach 2:
The patent uses digital copying of the microstructural pattern through optical imaging. The digital image serves as the identifier, eliminating the need for physical marking processes and reducing system complexity while maintaining high identification speed.
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
Enables automatic high-speed recording and identification of products, providing a robust solution for tracking, identification, and counterfeit detection without the need for visible markings, suitable for industries like pharmaceuticals, electronics, and luxury goods.
Implementation Method 1
The microstructure of the material surface serves as a unique identifier... optical imaging to capture and analyze the unique microstructure
Data Source
AI summary
The present application concerns the visual identification of materials or documents for tracking or authentication purposes. It describes methods to automatically authenticate an object by comparing some object images with reference images, the object images being characterized by the fact that visual elements used for comparison are non-disturbing for the naked eye. In some described approaches it provides the operator with visible features to locate the area to be imaged. It also proposes ways for real-time implementation enabling user friendly detection using mobile devices like smart phones.