Surface Microstructure Optical Identification for Anti-Counterfeiting
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Solution Overview
Problem
Current methods for tracking, tampering detection, and counterfeiting rely heavily on physical markings or unique identifiers, which can be costly and prone to counterfeiting.
Innovation Solution
The use of optical images of the microstructure of a product's surface for unique identification, eliminating the need for physical markings by matching acquired images with a database of previously recorded images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical markings or unique identifiers are used for tracking and identification, then product identification capability is improved, but manufacturing cost increases and susceptibility to counterfeiting worsens
Solution Approach 1:
The material surface itself serves as the identifier through its inherent microstructure, eliminating the need for external marking systems. The natural variations in material microstructure automatically provide unique identification without requiring additional manufacturing steps for applying markers, tags, or codes.
Solution Approach 2:
The identification function is extracted from separate physical markings and embedded directly into the material's intrinsic microstructure. By capturing and storing images of the natural surface variations, the patent removes the need for additional identification components while maintaining unique product identification.
2Measurement precision
If physical markings or unique identifiers are used for tracking and identification, then product identification capability is improved, but vulnerability to counterfeiting worsens
Solution Approach 1:
The material's own microstructure provides the identification signature, making it inherently difficult to counterfeit. Since the microstructure is intrinsic to the material and captured during manufacturing, replicating it requires reproducing the entire material structure rather than simply copying a surface marking.
Solution Approach 2:
The identification data is captured and stored in a database before the product reaches the consumer. By pre-registering the microstructure images during manufacturing, the system establishes a reference database that enables verification of authenticity, preventing counterfeiting by comparing future products against these predetermined references.
3Measurement precision
If traditional marking methods are used for product identification, then unique identification is achieved, but identification speed worsens
Solution Approach 1:
The patent replaces mechanical reading methods (such as optical character recognition of printed codes) with automated image capture and comparison systems. Digital imaging and database matching enable rapid identification without manual intervention, significantly increasing identification speed while maintaining accuracy.
Data Source
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AI summary
The present application concerns the visual identification of materials or documents for tracking purpose. The invention proposes a method to automatically identify an object by the following steps : - digitally acquiring a two-dimensional image through sampling on a uniformly spaced orthogonal grid of at least one color component of an area of interest of its surface illuminated by a non-coherent light which location, resolution, imaging angle and lighting angle are optimized for a given image matching metric, - comparing the acquired image to stored digital images of the same area, such comparison including the steps of : ∘ preprocessing the image, ∘ flattening the image, ∘ applying a rotation compensation procedure, ∘ applying a translation compensation procedure, ∘ masking the areas of interest ∘ computing a metric according to a deterministic convergence behavior when the mean square error between the acquired and recorded image tends towards a constant, such metric being dependent on the acquired and stored image resolutions and enabling the identification from the recorded images of a matching set of images for a given object image, the metric and threshold having the property that the cardinality of said matching set converges towards singleton when the resolution increases.