Counterfeit ID Detection via IR Character Count Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for detecting forgery in identification documents with IR-absorbing personalized data are inadequate, particularly when the data field is overprinted or pasted over with additional IR-absorbing data, as they rely solely on the presence of IR-absorbing features to distinguish originals from forgeries.
Innovation Solution
A method involving reading the data field with an IR reader, determining the number of alphanumeric characters, calculating an expected value based on the field's length and character size, and comparing it to generate a test signal if the character count exceeds the expected value, thereby detecting potential forgeries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If only the presence of IR-absorbing features is checked to detect forgeries, then the detection method is simple, but it fails to detect forgeries where the data field is overprinted or pasted over with additional IR-absorbing data
Solution Approach 1:
The patent changes the detection parameter from a simple binary check (presence/absence of IR-absorbing features) to a quantitative analysis of character count. By counting the number of alphanumeric characters in the IR-absorbing data and comparing it against an expected value, the system can detect forgeries where additional data has been overprinted, as these will have character counts exceeding the expected value for the original document.
2Measurement precision
If the character count method is used to detect forgeries, then detection accuracy improves, but the complexity of the detection process increases due to additional processing steps
Solution Approach 1:
The patent replaces complex manual or mechanical verification processes with automated image processing and character recognition algorithms. The IR image of the data field is processed by a reader that automatically counts alphanumeric characters and compares the count against expected values, eliminating the need for manual inspection while maintaining high detection precision.
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 effectively identifies forgeries by differentiating between original and forged IR-absorbing data sets, reducing errors and improving detection accuracy by using image processing to recognize IR-absorbing areas and transparent areas under IR light.
Implementation Method 1
data fields with IR-absorbing personalized data
Implementation Method 2
reading the data field with an IR reader
Data Source
Figure 1~2
AI summary
The invention relates to a method for counterfeit detection of identification documents which contain data fields having IR-absorbing personalized data, and to an associated computer program or computer-readable storage medium. The method comprises the following steps: (i) reading out a data field, which contains an IR-absorbing personalized data set, using an IR reading device; (ii) determining a number of alphanumerical characters in the read-out data field in an evaluation unit; and (iii) providing an expected value for the data field, which contains the IR-absorbing personalized data set, in the evaluation unit, wherein the expected value is determined as a function of a predetermined number of characters which are to be expected in the data field, or wherein additionally a length of the read-out data field is determined and a maximum number of characters is calculated on the basis of the length and a predetermined average character size, which are to be expected in the data field, the expected value being determined as a function of the calculated maximum number of characters; and (iv) comparing the determined number of characters with the expected value with regard to this data field in the evaluation unit, and generating a test signal in the event that the number of characters exceeds the expected value.