Document Authentication Using UV Imaging and ROI Color Profiles
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional document authentication methods are prone to human error and device inconsistencies, leading to false negatives due to variations in documents and imaging devices, and lack robustness in pattern matching processes.
Innovation Solution
A system that utilizes UV illumination and transforms document images from RGB to YCbCr color space, divides them into regions of interest (ROIs), generates color profile descriptors, and compares these descriptors with enrolled templates to determine authenticity, using polar histograms for enhanced precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If human eye inspection is used for document authentication, then the system is simple and easy to operate, but it is vulnerable to human error and lacks reliability
Solution Approach 1:
The patent replaces the mechanical human eye inspection system with an automated computer-based imaging and analysis system. The system uses digital imaging devices to capture document images and automatically analyzes security features, eliminating human error while maintaining operational simplicity through automated processing.
Solution Approach 2:
The patent introduces an intermediary automated analysis system that acts as a mediator between the document and the authentication decision. This intermediary system processes images through multiple analysis stages including color space transformation, feature extraction, and pattern recognition to provide reliable authentication results.
2Productivity
If simple pattern matching is used in computer-based authentication, then the system is fast and efficient, but it produces false negatives due to document variations and device inconsistencies
Solution Approach 1:
The patent divides the authentication process into multiple segmented stages: image capture, color space transformation, region of interest identification, feature extraction, and pattern matching. This segmentation allows each stage to be optimized independently, maintaining speed while improving accuracy through progressive filtering and analysis.
Solution Approach 2:
The patent transforms images from RGB to YCbCr color space to enhance the visibility and analysis of security features. This parameter change in color representation allows the system to better distinguish authentic security features from document variations, reducing false negatives while maintaining processing efficiency.
3Device complexity
If device variations and document aging are not accounted for, then the authentication system is simple, but it produces false negatives due to fading, wear and tear
Solution Approach 1:
The patent performs preliminary color space transformation and feature extraction to establish baseline characteristics of security features before pattern matching. This preliminary action allows the system to account for document aging and wear by comparing current features against established patterns, reducing false negatives without significantly increasing system complexity.
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
Improves document authentication accuracy by minimizing false negatives and accounting for device variations, while requiring minimal resources and processing time.
Implementation Method 1
a first image of the subject identification document, the first image depicting, in a red-green-blue (RGB) color space, the subject identification document illuminated by ultraviolet (UV) light
Data Source
AI summary
A system for authenticating a subject identification document includes instructions causing a processor to receive a first image of the document, depicting, in RGB color space, the document illuminated by UV light, and transform the first image to a second image in YCbCr color space. The instructions cause the processor to divide the second image into regions of interest (ROIs), and, for each ROI, generate a color profile descriptor including first data elements associated with pixel color in the YCbCr color space, and second data elements associated with pixel intensity of pixels within the ROI. The instructions also cause the processor to generate a score for the second image based on a comparison of the color profile descriptor for each ROI to a corresponding ROI of an enrolled document template, and compare the score to a threshold to determine whether the document is authenticated.