Authenticity Image Collation With Time-Based Density Correction
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Solution Overview
Problem
Existing simple information media, such as visitor cards, are susceptible to forgery and suffer from decreased collation accuracy due to staining or scratching, making high-security authentication challenging.
Innovation Solution
An authenticity collation system and method that uses a simple information medium, involving an issuing apparatus to print a collation image on a substrate and a collation apparatus to perform density correction and collation based on captured images, predicting density changes over time to determine a collation region using pixel differences and spatial frequency characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a simple information medium (printed substrate) is used instead of an IC card, then cost and issuance time are reduced, but security and anti-forgery capability deteriorate
Solution Approach 1:
The collation image is divided into multiple pixel regions, and collation is performed by comparing pixel values in specific regions. This segmentation allows the system to verify authenticity through detailed pixel-level analysis rather than simple overall image matching, enhancing security while maintaining the simplicity of printed substrates.
Solution Approach 2:
The patent applies different collation strategies to different regions of the collation image. Specific pixel regions are selected for collation based on their uniqueness and resistance to forgery, rather than treating the entire image uniformly. This local quality approach enhances security by focusing on the most distinctive and hard-to-reproduce areas.
2Measurement precision
If density correction is performed to improve collation accuracy, then collation precision improves, but processing time and computational complexity increase
Solution Approach 1:
Density correction values are calculated and stored in advance for different elapsed times. When collation is performed, the system simply retrieves the pre-calculated correction value corresponding to the measured elapsed time, rather than performing complex density calculations in real-time. This preliminary action significantly reduces processing time while maintaining high collation accuracy.
Solution Approach 2:
The system uses the elapsed time itself as a key to select the appropriate density correction value. The correction process becomes self-service, automatically adapting to the age of the information medium without requiring manual intervention or complex real-time analysis, thus balancing accuracy with efficiency.
3Reliability
If the collation region is expanded to include more areas, then collation reliability improves, but susceptibility to stains and scratches increases
Solution Approach 1:
The patent selects specific local pixel regions for collation that are optimized for authenticity verification. These regions are chosen to maximize uniqueness and minimize exposure to potential damage areas, achieving high reliability through strategic regional selection rather than comprehensive area coverage.
Solution Approach 2:
The patent replaces physical inspection methods with digital image processing and pixel value comparison. By using computational analysis of captured images, the system can accurately collate authenticity without physically contacting or potentially damaging the information medium, thus reducing susceptibility to surface damage during the collation process.
Data Source
AI summary
An authenticity collation apparatus for collating authenticity of an information medium on which a collation image is printed is proposed. The authenticity collation apparatus includes a processor configured to acquire a second captured image obtained by capturing the collation image at a time of collation, and determine a collation region for collation between a first captured image obtained by capturing the collation image at a time of issuance of the information medium and the second captured image, based on prediction information of a density change at a time point of acquiring the second captured image, the prediction information being based on an elapsed time from a time point of acquiring the first captured image.