Microscopic Texture Authentication via Digital Fingerprinting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current technologies lack effective and cost-efficient methods for uniquely identifying textures at a microscopic level across various materials, failing to address the significant issue of counterfeit goods and documents, which result in substantial market losses.
Innovation Solution
The system utilizes a fingerprinting mechanism that captures and compares microscopic texture images using partially coherent light, converting them into low-dimensional representations for similarity analysis, enabling unique identification of materials like fabric, paper, and metal through invariant GaborPCA and gradient histogram feature detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If microscopic texture imaging is used for authentication, then identification accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent creates a digital copy of the microscopic texture pattern and compares it with a reference copy stored in a database. This copying approach allows authentication without requiring complex physical measurement devices, as the microscopic images are captured and stored as digital data that can be compared through computational algorithms.
Solution Approach 2:
The patent replaces complex mechanical microscopic imaging equipment with a simplified system that uses standard digital cameras or smartphones to capture microscopic textures. The authentication process is then performed through computational comparison algorithms rather than complex mechanical measurement systems, reducing device complexity while maintaining identification accuracy.
2Adaptability or versatility
If microscopic texture analysis is applied to multiple materials, then versatility is improved, but measurement precision requirements increase
Solution Approach 1:
The patent adjusts the authentication threshold parameter based on the specific material being analyzed. Different materials have different texture characteristics, so the similarity threshold is dynamically modified to match the expected variation in each material type. This allows the system to maintain high precision across diverse materials without requiring a single fixed high-precision threshold for all materials.
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 allows for the authentication and verification of physical objects by determining if microscopic texture patterns match within a predetermined threshold, effectively addressing the challenge of counterfeit detection across different materials and conditions.
Implementation Method 1
when partially coherent light falls onto an object, the scattered light when projected to a screen can produce bright and dark regions
Data Source
AI summary
Exemplary methodology, procedure, system, method and computer-accessible medium can be provided for authenticating a non-digital medium of a physical object, by receiving at least one image of video of at least one marked or unmarked region, and comparing the first microscopic image or video of at least one marked or unmarked region with at least one second microscopic image or video relating to the non-digital medium to determine if a similarity between the first and second microscopic images or videos matches or exceeds a predetermined amount.