Coin Validation Using Weighted Error Correlation
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Solution Overview
Problem
Existing coin recognition and validation systems face challenges in distinguishing between genuine and counterfeit coins due to variations in coin types and wear, especially when similarities between coins are substantial compared to differences.
Innovation Solution
The use of a weighted error correlation coefficient algorithm in conjunction with inclined rail and sensor systems to measure and validate coins, incorporating magnetic and optical sensing with feature extraction and signal processing to determine coin authenticity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional coin recognition devices are used, then coin validation can be performed, but the ability to distinguish between genuine and counterfeit coins deteriorates due to variations in coin types and wear
Solution Approach 1:
The patent segments the coin validation process into multiple independent measurement stages: initial coin type identification, wear pattern analysis, and counterfeit detection. Each stage uses specific sensor arrays targeted at particular coin features, allowing the system to progressively refine its assessment rather than relying on a single comprehensive measurement that must handle all variations simultaneously.
Solution Approach 2:
The system dynamically adjusts measurement parameters based on the coin being validated. It changes sensing frequencies, threshold values, and analysis algorithms according to the detected coin type, denomination, and observed wear patterns. This allows optimal measurement conditions for each specific coin while maintaining sensitivity to counterfeit characteristics.
2Measurement precision
If more sensors are added to improve coin recognition accuracy, then measurement precision improves, but device complexity increases
Solution Approach 1:
The sensor array is configured to dynamically activate specific sensors based on the coin type and validation stage. Not all sensors operate simultaneously or at full capacity for every coin; instead, the system adapts which sensors are active and at what sensitivity levels, reducing overall system complexity while maintaining high measurement precision when needed.
Solution Approach 2:
Each sensor in the array is designed to serve multiple functions across different validation stages. The same magnetic sensors used for initial coin type identification are also employed for counterfeit detection and wear analysis. This multi-functionality reduces the total number of sensors required compared to a system with dedicated sensors for each measurement task.
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 enhances the sensitivity and accuracy of coin recognition and validation without requiring additional complex sensors, effectively differentiating between various coin denominations and types, including foreign currency, by analyzing distinctive features and trends.
Implementation Method 1
an inclined rail to roll coins and other similar objects
Implementation Method 2
incorporating magnetic and optical sensing
Implementation Method 3
incorporating magnetic and optical sensing
Data Source
AI summary
A method of examining a coin for determining the validity of its denomination, comprises the steps of moving a coin through a passageway, sensing said moving coin in said passageway with one or more sensors to interact with said moving coin and provide at least two values indicative of the said coin, calculating two or more coin features by using said at least two values, determining that said coin features values lie between predetermined minimum and maximum stored values, applying predetermined coefficients of weighted-error to each of said coin features, calculating weighted-error correlation coefficients using two or more of the said coin feature values, and determining validity when the said calculated weighted-error correlation coefficient is above predetermined minimum stored values, or when said coefficient is the maximum of all calculated coefficients.