2D Code Embedding in Images via Subblock Optimization
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Solution Overview
Problem
Existing methods for embedding two-dimensional (2D) codes, such as QR codes, into graphic images fail to improve aesthetics while maintaining decodability, resulting in visual artifacts and uneven distribution of the image within the code.
Innovation Solution
A method that subdivides both the graphic image and the 2D code into subblocks, identifies suitable pixels for modification, and applies a probability of detection model to optimize luminance values, ensuring minimal visual distortion and maintaining decodability by using a halftoning mask and priority matrix to simulate smooth blending between the code and image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If simple replacement method is used to embed image into QR code, then embedding process is simple, but visual quality deteriorates with coarse structure and undesirable artifacts
Solution Approach 1:
The QR code is divided into multiple sub-blocks, and each sub-block is processed independently to determine which pixels should be modified. This segmentation allows for fine-grained control over the embedding process, enabling high visual quality while maintaining systematic processing.
Solution Approach 2:
Different pixels within the QR code are treated differently based on their local characteristics. The patent identifies specific pixels for modification within each sub-block rather than uniformly modifying all pixels, creating local variations in quality that optimize both visual appearance and decodability.
2Shape
If image area ratio is increased to improve visual appearance, then aesthetic appeal improves, but decodability reliability deteriorates
Solution Approach 1:
Instead of modifying all pixels or a large uniform area, the patent modifies only specific pixels within sub-blocks that are identified as suitable for modification. This partial action approach allows image embedding while preserving enough of the original QR code structure to maintain decodability.
Solution Approach 2:
The patent changes parameters such as the area ratio of modified pixels and the distribution pattern of modified pixels to optimize the balance between visual appearance and decodability. By adjusting these parameters, the system achieves high aesthetic appeal while maintaining reliable decoding.
3Device complexity
If uniform pixel modification is applied across the QR code, then processing is simple, but visual distortion increases with coarse structure
Solution Approach 1:
The QR code is divided into multiple sub-blocks, and each sub-block is processed independently to determine which pixels should be modified. This segmentation allows for fine-grained control over the embedding process, enabling high visual quality while maintaining systematic processing.
Solution Approach 2:
The pixel modification process is made dynamic rather than static. The patent adaptively determines which pixels to modify based on local characteristics and decodability requirements, rather than applying a fixed uniform modification pattern across the entire QR code.
Data Source
AI summary
Disclosed are a method and apparatus for embedding a graphic image representation into a two dimensional matrix code by modifying the characteristic values of individual pixels in the image according the values of a provided two dimensional matrix code image. The modified character pixel values are determined using an optimization procedure that minimizes a visual distortion with respect to the original graphic image representation while maintaining the value of a probability of error model below a specified limit.