Object Authenticity Verification via Random Feature Fingerprinting
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Solution Overview
Problem
Current methods for verifying the authenticity of objects, such as banknotes and medications, are inefficient and unreliable, particularly in distinguishing genuine from forged items, and lack user trust due to dependency on Level 1 and Level 2 security features that can be difficult to verify without specialized tools.
Innovation Solution
A method and device that utilize optically recognizable random features unique to each object, generating a fingerprint through image processing, allowing for secure and unambiguous verification by comparing test object fingerprints with reference fingerprints, optionally combined with identification codes, using a client-server approach for scalable and robust authenticity checks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional security features (Level 1 and Level 2) are used for object verification, then the verification process becomes complex and requires specialized tools, but the reliability and user trust remain low because these features are difficult to verify without specialized equipment
Solution Approach 1:
The patent replaces complex mechanical verification systems with optical field-based verification. Instead of using specialized tools and equipment to detect security features, the invention uses optical imaging to capture random surface features and generates digital fingerprints for comparison. This substitution of mechanical verification with optical field analysis simplifies the verification process while improving reliability and user trust.
2Reliability
If extensive security features are added to objects for verification purposes, then the authenticity verification becomes more reliable, but the manufacturing complexity and cost increase significantly
Solution Approach 1:
The patent extracts the verification function from complex physical security features and transfers it to digital fingerprint analysis. Instead of embedding extensive security elements in objects, the invention captures random surface features that naturally exist on all objects and converts them into verification data. This extraction approach maintains verification reliability while eliminating the need for complex manufacturing processes.
Solution Approach 2:
The patent replaces expensive, complex security features with simple, naturally occurring random surface features that require no additional manufacturing cost. These random features are inherently present on all objects and can be captured using standard imaging devices, making verification accessible without increasing manufacturing complexity or cost.
3Difficulty of detecting and measuring
If specialized tools and equipment are used for verification, then the detection capability improves, but the ease of operation and accessibility for average users deteriorates
Solution Approach 1:
The patent enables verification devices to perform self-verification by capturing images of objects and automatically generating and comparing digital fingerprints. The system uses standard imaging components already present in mobile devices to detect and analyze random surface features, eliminating the need for specialized external tools. This self-service approach maintains high detection capability while significantly improving ease of operation for average users.
Data Source
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AI summary
The invention relates to a method for verifying the authenticity of an object (OBJ), wherein the object (OBJ) has optically detectable random features unique to the object (OBJ). The method comprises a step of reading image data (103), representing at least a subsection (301) of the object (OBJ), from an interface (111) to an image acquisition device (102) of a device (100) for object evaluation. The method also comprises a step of processing the image data (103) using a processing instruction (113) according to which a plurality of signature values for a plurality of pixels of an image region of the image data are determined in order to generate a test object fingerprint of the object (OBJ) as verification data (115) for comparison with a reference object fingerprint.