Mobile IR Camera Bill Counterfeit Detection via Image Correction
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Solution Overview
Problem
Conventional methods for identifying counterfeit bills using mobile IR cameras are affected by user capturing motion and ambient environment, leading to degraded image quality and inaccurate detection.
Innovation Solution
A mobile communication device and method that receives an IR image, generates a binary image, and compares it to a pre-stored real bill database, correcting for user motion and ambient effects by moving, rotating, enlarging, or contracting the image to match the database, determining a bill as counterfeit based on the number of displayed pixels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a mobile IR camera is used for counterfeit detection, then the device portability and ease of operation are improved, but the measurement precision and reliability are degraded due to user capturing motion and ambient environment effects
Solution Approach 1:
The system pre-stores reference images of real bills in a database before actual detection occurs. During detection, the captured image is compared against these pre-prepared references, allowing the system to compensate for motion and environmental variations by matching key features against the stored reference patterns.
Solution Approach 2:
The system captures an image, compares it with the reference database, identifies discrepancies, and uses this feedback to determine authenticity. The comparison process provides feedback on which features match or mismatch, enabling the system to make accurate counterfeit detection decisions despite image quality variations.
2Device complexity
If conventional visual inspection methods are used, then the device complexity is reduced, but the reliability of counterfeit detection is insufficient without prior knowledge of anti-counterfeiting features
Solution Approach 1:
The system creates a digital copy (image) of the bill and compares it against stored reference copies of authentic bills. This copying approach allows automated comparison of anti-counterfeiting features without requiring the user to manually know or check specific security features, thereby maintaining simplicity while improving reliability.
Solution Approach 2:
The system introduces an intermediary comparison process between the captured bill image and the reference database. This intermediary automated comparison mechanism handles the complex task of verifying anti-counterfeiting features, allowing the device to remain simple to operate while achieving high detection reliability.
3Reliability
If image correction and comparison algorithms are implemented, then the reliability and measurement precision are improved, but the device complexity and computation requirements increase
Solution Approach 1:
The system extracts only the essential comparison functionality needed for counterfeit detection - capturing an image, comparing it with the reference database, and determining authenticity. By taking out only the necessary computational steps and implementing them efficiently, the system achieves high reliability without requiring excessively complex algorithms or high-performance computing resources.
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
The solution effectively suppresses the effects of user motion and ambient environment, allowing accurate counterfeit detection without complex algorithms, making it suitable for devices with limited computation resources and enhancing detection reliability and speed.
Implementation Method 1
a camera module configured to receive a captured IR image of a bill
Data Source
AI summary
An apparatus for identifying a counterfeit bill is provided. The apparatus includes a camera module configured to receive a captured IR image of a bill; a binary image generator configured to generate a binary image of the bill, based on the IR image; a distance value calculator configured to compare a predetermined area of the binary image with a predetermined area of a pre-stored real bill database corresponding to the predetermined area of the binary image; and a corrected image generator configured to generate a corrected image based on a result of the comparison.