2D Optical Code Decoding With Composite Image Reliability Filtering
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Solution Overview
Problem
Current methods for decoding two-dimensional optical codes, especially when based on a single image, are inefficient when the code is partially damaged or on reflective surfaces, leading to long waiting times and slower decoding due to the limitations of error correction algorithms like Reed Solomon.
Innovation Solution
A decoding method that combines images by assigning an undefined value to codewords that do not meet a reliability threshold, thereby reducing the likelihood of erroneous codewords and enhancing the efficiency of error detection and correction algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If error correction algorithms like Reed Solomon are applied to decode a single image, then decoding can succeed for partially damaged codes, but decoding time increases and productivity decreases when the code is on reflective surfaces or heavily damaged
Solution Approach 1:
The patent combines multiple images of the same code into a single composite image before decoding. By merging the information from multiple images, the system creates a more complete and accurate representation of the code, reducing the impact of damage or reflective surface interference. This allows the error correction algorithms to work more effectively and reduces the need for multiple separate decoding attempts, thereby improving both reliability and productivity.
2Reliability
If multiple images are acquired and combined to improve decoding accuracy, then decoding success rate increases, but the complexity of the decoding system increases
Solution Approach 1:
The patent performs preliminary actions by acquiring multiple images and combining them into a composite image before the actual decoding process. This preliminary combination step prepares the data in an optimal state for decoding, reducing the complexity of the error correction algorithms needed and simplifying the overall system architecture while maintaining high decoding success rates.
3Reliability
If the Reed Solomon algorithm is used for error detection and correction, then codes on reflective surfaces can be decoded, but the processing time increases significantly
Solution Approach 1:
By combining multiple images into a composite image before decoding, the system performs a preliminary action that reduces the number of errors and ambiguities in the data. This preprocessing step means that when the Reed Solomon algorithm is applied, it has less work to do and can correct fewer errors, significantly reducing the processing time while maintaining the ability to decode codes on reflective surfaces.
Data Source
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AI summary
Method for decoding a two-dimensional optical code formed by a set number of codewords, wherein decoding the code based on a single acquired image has not been successful, comprises analysing an acquired image and at least one further acquired image and obtaining a respective set and further set of values of identified codewords. Each codeword can take on either an undefined value or vice versa a numeric value if the codeword is recognised. A combined set of codewords is created and each codeword of the combined set is assigned a value of a codeword of the set and/or of the further set and an algorithm for detecting and self- correction of errors is applied to the combined set to obtain confirmation of successful decoding of the two- dimensional code. Combining the set and the further set of codewords comprises, for each codeword of said combined set, comparing corresponding codewords of the set and further set and if corresponding codewords have a different respective numeric value and further numeric value and said codeword of said combined set is identified as unreliable, the codeword of the combined set is assigned an undefined value to make the check more efficient by applying the algorithm for error detection and self -correction.