Optical Code Reading with Prefabricated Scheme Correction
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Solution Overview
Problem
Existing methods for reading optical codes are prone to errors due to the complexity and effort required in preparing lists of regular expressions, leading to incomplete or incorrect schemes that can introduce additional errors, and lack robustness in handling various code situations.
Innovation Solution
A method using a prefabricated catalog of schemes, selected and tested by experts, which are automatically activated based on a teaching phase that evaluates the frequency of matching schemes, ensuring their relevance and reliability for the specific application, and includes additional functions like OCR for clear text recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a list of regular expressions is manually prepared for code correction, then the reading reliability can be improved, but the preparation effort and complexity increase significantly
Solution Approach 1:
The patent pre-generates a comprehensive catalog of schemes during a teaching phase by analyzing historical code data. This preliminary action creates a ready-to-use repository of correction patterns that can be automatically selected during operation, eliminating the need for manual regular expression preparation while maintaining high reading reliability through pre-validated schemes.
Solution Approach 2:
The system automatically generates and optimizes its own scheme catalog by analyzing its own historical reading data. The teaching phase enables the system to self-improve by identifying frequently occurring code patterns and generating appropriate correction schemes without external intervention, thereby reducing preparation complexity while improving reliability through data-driven optimization.
2Reliability
If manual preparation of correction schemes is performed, then reading errors can be reduced, but the time and expertise required increase
Solution Approach 1:
The system performs preliminary scheme generation during a teaching phase by analyzing historical code readings and automatically creating a catalog of correction patterns. This pre-computation eliminates the need for time-consuming manual scheme preparation in production environments, while the automated analysis ensures reading accuracy through objectively derived schemes rather than subjective manual creation.
Solution Approach 2:
The patent replaces the manual mechanical process of creating regular expressions with an automated computational system. The teaching phase uses algorithms to analyze code patterns and generate schemes automatically, substituting human expertise and manual effort with machine-based pattern recognition and generation, thereby reducing preparation time while maintaining or improving reading accuracy.
3Ease of operation
If a fixed list of schemes is used, then the system is simpler to operate, but it cannot adapt to changing code patterns
Solution Approach 1:
The system implements dynamics by enabling the scheme catalog to be generated and updated based on actual code reading data during a teaching phase. Rather than using a static fixed list, the system adapts its scheme catalog to match the specific code patterns encountered in the application environment, maintaining ease of operation through automated selection while achieving adaptability through data-driven scheme generation.
Solution Approach 2:
The teaching phase incorporates feedback mechanisms where the system analyzes historical code reading results and uses this information to generate optimized schemes. The system learns from past performance and adjusts its scheme catalog accordingly, creating a feedback loop that improves adaptability to specific code patterns while keeping the operational interface simple and automated for the user.
Data Source
AI summary
A method of reading an optical code is provided that encodes a message that has a character chain having a plurality of characters, said method comprising the steps: of recording image data having the optical code; evaluating the image data by reading the message; comparing the read characters of the message with at least one scheme that contains a character for at least one position of the message that is expected at this position in codes to be read; and checking or correcting the read message based on a scheme matching the message after the comparison. A prefabricated catalog of schemes is provided here and a subset of the schemes of the catalog is activated for the comparison with the read characters of the message.