Barcode Chart Imaging for Robust Optical Resolution Testing
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Solution Overview
Problem
Existing methods for determining optical resolution in camera systems are inadequate, particularly in dynamic scenes and under varying illumination conditions, and lack robustness in decoding barcode images.
Innovation Solution
A computing device processes images of barcode charts with varying barcode attributes to determine resolution metrics by fitting a parametric model to decode rates, considering factors like barcode orientation, size, and illumination changes, allowing for lens selection based on target decode rates and evaluating camera sensor performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional MTF methods are used to measure optical resolution, then the measurement process is simple, but the method fails to provide robust and accurate resolution determination in dynamic scenes and under varying illumination conditions
Solution Approach 1:
The patent changes the measurement parameters from traditional MTF methods to barcode-based resolution testing. By using barcodes with known dimensions and patterns, the system determines optical resolution through barcode decoding accuracy rather than contrast modulation, enabling robust performance across dynamic scenes and varying illumination conditions.
Solution Approach 2:
The patent uses barcode charts as standardized test targets that replicate known patterns. By capturing images of these barcode charts and comparing the decoded information against known values, the system creates a reliable copy-based measurement approach that works reliably under diverse imaging conditions.
2Reliability
If barcode charts with varying barcode attributes are used to determine resolution metrics, then the robustness and accuracy of optical resolution determination is improved, but the complexity of the measurement process increases
Solution Approach 1:
The patent segments the barcode chart into multiple test patterns with varying barcode attributes (different sizes, orientations, and contrast levels). Each segment tests a specific aspect of optical performance, allowing the system to evaluate resolution metrics systematically while maintaining manageable processing complexity through structured test design.
Solution Approach 2:
The system incorporates feedback by comparing the decoded barcode information against known reference values. This feedback mechanism allows the system to automatically determine resolution metrics based on decoding accuracy, simplifying the measurement process while maintaining high reliability through automated verification.
3Measurement precision
If the optical resolution is determined using barcode decode rates and parametric models, then the accuracy of resolution metrics is improved, but the computational processing requirements increase
Solution Approach 1:
The patent transforms the measurement problem into a parameter estimation task by fitting a parametric model to barcode decode rate data. By changing from direct image analysis to statistical parameter fitting, the system achieves high measurement precision while controlling computational requirements through efficient modeling approaches.
Solution Approach 2:
The system uses the barcode chart itself as the test target without requiring external calibration equipment or complex setup. The barcode patterns encode the ground truth information, allowing the system to self-verify and self-calibrate, thereby reducing the need for additional computational resources and complex processing pipelines.
Data Source
AI summary
Techniques for optical resolution determination from barcode chart images are described herein. In an example, a computer system receives an image captured by an image acquisition system having a camera with a lens. The image is of a chart including barcode sets arranged in one or more orientations with respect to an optical axis of the camera, and individual barcodes of a barcode set have a barcode attribute. The computer system decodes the barcode sets in the image using a barcode decoder. The computer system determines, for individual barcode attributes and for individual orientations, a number of decoded barcodes in the barcode sets that match encoded information stored in a barcode manifest. The computer system determines a resolution metric of the image acquisition system for a target barcode decode rate based on a distribution of a decode rate associated with the barcode attribute for the decoded barcodes.