Barcode Edge Field Adjustment for Distortion-Aware Decoding
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Solution Overview
Problem
Current barcode reading technologies face inefficiencies due to 'brute-force' methods like jittering, which increase decoding time and degrade accuracy when dealing with distortions from overprinting or overexposure, leading to unnecessary edge field variants and reduced readability.
Innovation Solution
A method that adjusts the edge field based on the similarity between bar and gap width distributions, generating adapted edge fields only when distortions are detected, using similarity values to determine if adjustments are needed, thereby reducing decoding load and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the jittering method is used to generate multiple edge field variants, then the success rate in problematic reading situations improves, but the decoding time increases significantly
Solution Approach 1:
The patent applies preliminary action by performing a similarity check on the captured barcode image before generating multiple edge field variants. The system calculates a similarity value between the captured barcode and a reference barcode, and only proceeds to generate multiple variants if the similarity exceeds a threshold, indicating potential distortion. This preliminary filtering action prevents unnecessary processing in normal cases while maintaining reliability in problematic situations.
Solution Approach 2:
The patent changes the parameter of edge field generation from a fixed approach (always generating 3 variants) to a dynamic approach (generating variants only when similarity value indicates distortion). The system adjusts the number of edge field variants based on the calculated similarity parameter, transitioning from static to adaptive processing based on image quality assessment.
2Measurement precision
If multiple edge field variants are generated using jittering, then the accuracy in distorted barcodes improves, but unnecessary variants are created that degrade reading accuracy
Solution Approach 1:
The patent performs a preliminary similarity assessment before generating multiple edge field variants. By calculating the similarity value between the captured barcode and reference barcode in advance, the system identifies whether distortion is present. This preliminary action prevents the creation of unnecessary variants in normal cases, thereby avoiding the degradation of reading accuracy that occurs when inappropriate variants are generated.
Solution Approach 2:
The patent implements feedback by using the calculated similarity value to control the subsequent processing steps. The similarity metric provides feedback about image quality, and this feedback determines whether to proceed with multiple variant generation or use a single edge field. This closed-loop control ensures that variants are only generated when the feedback indicates distortion is present, preventing accuracy degradation.
3Reliability
If the brute-force jittering method is applied to all barcodes, then potential distortions are compensated, but the overall reading speed decreases
Solution Approach 1:
The patent applies preliminary action by performing a quick similarity check on all captured barcodes before applying the computationally intensive jittering method. This preliminary filtering step identifies which barcodes actually need distortion compensation, allowing the system to process normal barcodes quickly while applying full processing only when necessary, thereby maintaining overall reading speed.
Solution Approach 2:
The patent applies partial action by using the jittering method selectively rather than universally. Instead of applying excessive processing to all barcodes, the system applies partial processing (single edge field) to normal barcodes and full processing (multiple variants) only to distorted barcodes identified by the similarity check, optimizing the balance between reliability and productivity.
Data Source
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AI summary
The invention relates to a method for reading barcodes, comprising: capturing a barcode by means of an image capture device, the barcode element comprising barcode elements in the form of bars and spaces, wherein the bars and the spaces arranged between the bars are arranged alternately, wherein each bar and/or each space can be assigned to a width level of a predefined number of width levels, each width level having a respective reference width; generating an edge field based on the captured barcode, wherein an edge in the edge field indicates a bar-space transition; determining a similarity value using the edge field, which indicates a similarity between a distribution of bar width values and a distribution of space width values; and adjusting the edge field if the similarity value meets a predetermined condition.and the barcode is decoded based on the edge field and/or the adapted edge field.