Barcode Subpixel Alignment for Tilt Correction
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Solution Overview
Problem
Camera-based barcode readers face challenges in decoding barcodes due to misalignment and distortion caused by linear and non-linear distortions, low lighting conditions, and barcode quality issues, leading to reduced accuracy and increased operational delays in high-throughput environments.
Innovation Solution
A computer vision system with an alignment tool that evaluates pixel regions within a barcode image using different combinations of alignment parameters, including offset and scale adjustments, to correct tilt and skew, enabling precise alignment and decoding of barcodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If camera-based barcode readers are used to read barcodes in high-throughput environments, then productivity increases, but misalignment and distortion cause reduced decoding accuracy
Solution Approach 1:
The alignment tool performs preliminary alignment of the barcode image before decoding by evaluating pixel regions with different alignment parameters (offset and scale), determining optimal parameters, and adjusting the image. This preliminary action corrects misalignment and distortion caused by linear and non-linear effects, ensuring high decoding accuracy while maintaining high processing speed through automated parameter optimization
Solution Approach 2:
The system uses feedback from evaluating multiple alignment parameter combinations to determine the optimal offset and scale parameters. By comparing how well different parameter sets align the barcode image, the system iteratively refines the alignment before decoding, ensuring high accuracy even in high-throughput environments where speed is critical
2Measurement precision
If high-resolution image sensors and high-quality lenses are used to improve barcode image quality, then decoding accuracy improves, but device complexity and cost increase
Solution Approach 1:
Instead of relying on high-resolution hardware, the alignment tool changes the parameters of the captured image through computational alignment. By evaluating offset and scale parameters and applying the optimal transformation, the system corrects misalignment and distortion software-based, achieving high decoding accuracy with standard image sensors and lenses, thereby reducing device complexity and cost
3Measurement precision
If alignment parameters are evaluated for every pixel region to correct misalignment, then decoding accuracy improves, but processing time increases
Solution Approach 1:
The alignment tool segments the barcode image into multiple pixel regions and evaluates alignment parameters for each region independently. By processing regions in parallel and using efficient evaluation methods, the system achieves high alignment precision without excessive processing time, balancing accuracy and speed in high-throughput environments
Data Source
AI summary
A camera-based barcode reader captures an image, determines a region of interest of a barcode within the image, and generates a barcode image from the region of interest. The camera-based barcode reader aligns each of multiple horizontal regions within the barcode image to a reference horizontal region within the barcode image. The alignment of a horizontal region includes (i) determining a set of alignment parameters to apply to the horizontal region based on a comparison of the reference horizontal region to the horizontal region when adjusted to different combinations of alignment parameters and (ii) adjusting the horizontal region according to the set of alignment parameters for that horizontal region. After aligning the barcode image, the camera-based barcode reader decodes the barcode from the barcode image.