Image Erosion for Security Marker Authentication
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for authenticating security markers at low levels struggle with cross-talk from unintended materials, leading to inaccurate discrimination between intended and unintended signals due to differing emission profiles, especially in high spatial density regions.
Innovation Solution
An image erosion process is applied to security marker emissions, resulting in a single erosion ratio value that is compared to a threshold, where low spatial density markers pass and high spatial density markers fail, effectively distinguishing between intended and unintended emissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If security markers are applied at very low levels to detect genuine products, then authentication sensitivity is improved, but cross-talk from unintended materials increases leading to false positives
Solution Approach 1:
The patent applies morphological operations (erosion, opening) that selectively affect different spatial regions of the image based on local pixel density characteristics. Genuine markers with low spatial density retain their signal after erosion, while unintended materials with high spatial density are suppressed, achieving local differentiation that resolves the contradiction between sensitivity and reliability
Solution Approach 2:
The patent performs preliminary image processing steps (erosion, opening operations) before final authentication decision. These preliminary actions pre-process the image to eliminate high-density cross-talk signals before they can interfere with the authentication measurement, thereby maintaining both sensitivity to genuine markers and reliability by preventing false positives
2Measurement precision
If image processing is applied to distinguish intended markers from unintended materials, then discrimination accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent replaces complex spectral analysis or machine learning-based discrimination methods with simple morphological image processing operations (erosion, opening). These operations use basic logical comparisons and pixel operations that are computationally efficient while maintaining high discrimination accuracy between low-density genuine markers and high-density unintended 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 significantly reduces false positives by ensuring that only intended markers meet the erosion threshold, enhancing the accuracy of security marker authentication and reducing product counterfeiting and diversion detection.
Implementation Method 1
security markers applied at very low levels to objects which, when excited with light of appropriate wavelengths, emit radiation which produce a unique image
Data Source
AI summary
A method for detecting authorized security markers includes capturing an image of a region of interest on a product with a camera; storing image data in a two-dimensional array on a microprocessor; counting a number of pixels at or above a predetermined brightness level in the image data with the microprocessor to determine a first score; eroding the image data; counting the pixels which remain at or above the predetermined brightness level after erosion to determine a second score; calculating a ratio of the second score to the first score; and producing a first authentication signal if the ratio meets a first predetermined criteria.