Banknote Recognition Using Dual Threshold Judgment
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Solution Overview
Problem
Existing banknote recognition and counting machines require complex operations for authenticity and denomination judgment, including manual input of count results for reject banknotes, and struggle with accurately distinguishing between genuine and counterfeit banknotes, especially when banknotes are stained or have transport errors.
Innovation Solution
A banknote recognition and counting machine that uses two judgment threshold values to automatically differentiate between genuine and counterfeit banknotes, eliminating the need for manual input by outputting the total sum of count results for both judgment modes, and automatically re-judging banknotes with the second threshold value if initially rejected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single authenticity judgment threshold value is used to determine whether banknotes are genuine or counterfeit, then the judgment process is simple and fast, but stained banknotes or banknotes with transport errors are mistakenly judged as counterfeit, reducing accuracy
Solution Approach 1:
The authenticity judgment process is segmented into two distinct stages: first judgment using a first threshold value, and second judgment using a second threshold value. This segmentation allows the system to handle different types of banknotes differently - genuine banknotes are confirmed in the first stage, while potentially stained or error-containing banknotes are re-evaluated in the second stage with a more lenient threshold, thereby improving overall judgment accuracy without excessive complexity
Solution Approach 2:
The threshold value is made dynamic rather than fixed. The system automatically adjusts the threshold value based on the judgment result - using a first threshold for initial judgment and switching to a second threshold for re-judgment of rejected banknotes. This dynamic adjustment enables the system to adapt to different banknote conditions (clean vs. stained/error-containing) and improves measurement precision while maintaining operational simplicity
2Adaptability or versatility
If manual input of count results for reject banknotes is required, then flexibility in handling different judgment scenarios is improved, but operation complexity increases and productivity decreases
Solution Approach 1:
The system performs self-service by automatically re-judging reject banknotes using the second threshold value without requiring manual intervention. The control unit automatically identifies rejected banknotes, re-evaluates them with the alternative threshold, and integrates the results. This eliminates the need for manual count input while maintaining flexibility in handling different judgment scenarios, thereby improving productivity without sacrificing adaptability
Solution Approach 2:
The system implements a feedback mechanism where the judgment results from the first threshold evaluation are fed back into the system to trigger automatic re-judgment of rejected banknotes. The control unit uses the feedback from initial rejections to automatically initiate second-stage judgment, and then integrates these results to provide the final count. This closed-loop feedback system maintains operational flexibility while eliminating manual input requirements, thus improving productivity
3Productivity
If a lower authenticity judgment threshold is used to accept more banknotes, then more stained or error-containing banknotes are accepted, but the risk of accepting counterfeit banknotes increases
Solution Approach 1:
The judgment process is segmented into two sequential stages with different threshold values. The first stage uses a stricter first threshold to maintain high security and reject potential counterfeits. The second stage uses a more lenient second threshold to accept additional valid banknotes that may have been rejected in the first stage due to staining or transport errors. This segmentation allows the system to process more banknotes overall while maintaining reliability through the two-layer verification approach
Solution Approach 2:
The system performs a preliminary judgment using the first threshold value before applying the second threshold. This preliminary action filters out obvious counterfeits in the first stage, allowing the second stage to focus on re-evaluating only those banknotes that failed the first threshold but might still be genuine (e.g., stained or slightly damaged notes). This preliminary filtering action maintains reliability while enabling higher overall acceptance rates
Data Source
AI summary
Banknotes are taken into a banknote recognition and counting machine (10), a recognition and counting process for the banknotes is performed by a recognition and counting unit (24), judgment for the banknotes is performed by using a first judgment threshold value, based on the recognition result on each banknote recognized by the recognition and counting unit (24), and then the banknotes are fed, selectively, to a stacking unit (26) or reject unit (30), based on the judgment result on each banknote. Then the banknotes, respectively fed to the reject unit (30), are taken again into the banknote recognition and counting machine (10), the recognition and counting process for such banknotes is performed by the recognition and counting unit (24), and then the judgment for the banknotes is performed, by using a second judgment threshold value set smaller than the first judgment threshold value, based on the recognition result on each banknote recognized by the recognition and counting unit (24). Thereafter, information, which relates to the total sum of a count result on the banknotes, respectively judged to be true upon the judgment for the banknotes by using the first judgment threshold value and another count result on the banknotes, respectively judged to be true upon the judgment for the banknotes by using the second judgment threshold value, is output.