Halftone Image Data Embedding Without Reference Images
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Solution Overview
Problem
Existing methods for encoding information in printed matter, such as halftoning, require a reference image for data recovery, which limits their applicability and accuracy, especially when dealing with halftone images that have checkerboard subsampling, leading to unrecoverable data bits.
Innovation Solution
A method that embeds payload data into halftone images by shifting clustered-dot patterns without a reference image, using redundancy maps for error correction and alignment, allowing all cells to carry data and ensuring recoverability through scalable halftoning and ordered dithering techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If halftoning is used to encode information in printed matter, then data can be embedded in the image, but a reference image is required for data recovery which limits applicability and accuracy
Solution Approach 1:
The patent applies preliminary action by embedding alignment markers and redundancy information during the halftoning process itself, before the actual data encoding. This allows the receiver to perform self-alignment and error correction without needing the original reference image, thereby enabling data recovery in scenarios where the reference image is unavailable.
Solution Approach 2:
The invention implements self-service by designing a halftoning system that contains all necessary components for data recovery within the halftone image itself. The alignment markers and redundancy bits enable the system to autonomously perform alignment and error correction, eliminating the external dependency on reference images for data recovery.
2Productivity
If checkerboard subsampling is applied in halftone images, then processing efficiency is improved, but data bits become unrecoverable
Solution Approach 1:
The patent applies local quality by differentiating the treatment of different regions within the halftone image. Alignment markers are placed in specific locations that are preserved during subsampling, while redundancy bits are strategically positioned to compensate for potential data loss in other regions. This localized approach ensures that critical recovery information survives the subsampling process.
Solution Approach 2:
The invention implements beforehand cushioning by incorporating redundancy bits during the halftoning process, specifically designed to compensate for potential data loss from checkerboard subsampling. These redundant elements act as a buffer that ensures data recoverability even when some bits are lost during efficient subsampled processing.
3Quantity of substance
If all cells are used as information carriers, then data capacity is maximized, but error correction becomes more difficult
Solution Approach 1:
The patent applies segmentation by dividing the halftone image into distinct functional regions: alignment markers for positioning, redundancy bits for error correction, and data-bearing cells for information storage. This segmentation allows the system to maximize data capacity in the cell regions while dedicating specific structures to error correction, thereby managing complexity through functional separation.
Solution Approach 2:
The invention uses redundancy bits as an intermediary element that facilitates error correction across the entire image. These intermediary bits act as a buffer layer between the data cells and the error correction process, enabling the system to handle errors in a maximized-capacity configuration without requiring complex distributed error correction across all cells.
Data Source
AI summary
A data-bearing image (391) is created from a carrier image (371). The carrier image (371) is scaled to produce a scaled image. A clustered-dot halftone screen is applied to the scaled image to produce a halftone image. A resulting number of cells in the halftone image conforms to a cell count (372) that includes a horizontal cell value and a vertical cell value. Payload data is encoded into the halftone image to produce a data-bearing halftone image, including shifting pixel clusters within cells of the halftone image that include pixel clusters.