Color-Coded Barcode Data Transfer Reliability
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Solution Overview
Problem
Existing barcode technologies face decoding failures due to reader distortion, skewed viewing angles, and high error probabilities, especially with large error correction schemes that increase barcode size and reduce pixel density, limiting data capacity and reliability.
Innovation Solution
The development of color-coded barcodes with finder, position detection, alignment, and orientation patterns, along with a sharing scheme that divides data into chunks with redundancy, allowing for efficient decoding even under distorted conditions and increased data transfer rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If large error correction schemes are used to improve decoding reliability under distorted conditions, then error correction capability is improved, but barcode size increases and pixel density decreases
Solution Approach 1:
The patent divides the barcode into multiple independent zones (finder zone, position detection zones, alignment zones, data zones) with specific functions. This segmentation allows the error correction to be localized and optimized for each zone rather than applying uniform error correction across the entire barcode, thereby improving decoding reliability without proportionally increasing overall size.
Solution Approach 2:
The patent introduces orientation detection patterns and alignment patterns that operate in additional spatial dimensions beyond simple data storage. These patterns provide geometric reference frames that enable robust decoding under distortion without requiring excessive redundancy in the data portion, thus improving reliability while controlling size growth.
2Reliability
If forward error correction is increased to handle unreadable portions, then data recovery capability is improved, but pixel density decreases making decoding more error-prone
Solution Approach 1:
The patent applies different error correction strategies to different zones of the barcode. Critical zones like finder patterns and position detection patterns have built-in geometric redundancy that provides error tolerance without requiring high pixel density. Data zones use optimized forward error correction codes matched to their specific error probabilities, allowing reliable data recovery while maintaining adequate pixel density throughout.
Solution Approach 2:
The patent optimizes the error correction code parameters (such as Reed-Solomon code rates and lengths) specifically for the pixel density constraints of mobile device displays and camera sensors. By adjusting these parameters to match the actual operating conditions rather than using fixed conservative values, the system achieves reliable data recovery at lower pixel densities than traditional approaches.
3Measurement precision
If timing patterns and position detection patterns are added to facilitate decoding, then decoding accuracy is improved, but barcode complexity increases
Solution Approach 1:
The patent designs the finder pattern and position detection patterns to serve multiple functions simultaneously: they provide timing information for synchronization, position information for alignment, orientation information for rotation correction, and even serve as part of the error correction mechanism through their geometric redundancy. This multi-functionality reduces the need for separate dedicated patterns, thereby improving decoding accuracy while limiting complexity increase.
4Quantity of substance
If color coding is implemented to increase data capacity, then data storage capacity is improved, but decoding complexity under distortion increases
Solution Approach 1:
The patent uses color (or grayscale level) variations to encode additional data bits within the existing barcode structure. By utilizing multiple luminance levels rather than just binary black and white, the system increases data capacity without adding more physical zones or patterns. The color-coded modules maintain the same geometric structure as traditional barcodes, so decoding algorithms can be extended to handle multiple levels without proportionally increasing complexity.
Data Source
AI summary
Methods and systems for creating and using redundant and very high capacity barcodes are presented. An individual barcode can include one or more finder patterns, one or more position detection patterns, one or more alignment patterns, one or more orientation detection patterns, one or more format and version information patterns, and one or more modules, where each of these sections can be of a separate size, shape, color and location from the other of these sections. Each individual barcode can be encoded with a separate chunk of data. The individual barcodes can be combined into a composite barcode, which can have patterns and modules used can include many different sizes, shapes, colors and locations of such patterns and modules within the barcode. The individual and composite barcodes can be used to transfer data to a capture device. Original data can be expanded and divided into chunks of data. The chunks of data can be encoded into individual or composite barcodes and then sequentially displayed as a moving image. A device can capture each frame of the moving image of barcodes and decode them into chunks. The original data can then be derived from the decoded chunks of data.