Token-Based File Compression via Medial-Axis Transformation
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Solution Overview
Problem
Content providers face challenges in generating, storing, and transferring digital images of content due to inaccuracies in optical character recognition and high storage and transfer costs associated with large file sizes, particularly when reducing image resolution affects legibility.
Innovation Solution
A method and system for compressing token-based files by applying a medial-axis transformation to generate thinned tokens, grouping similar shapes, and selecting representative tokens for storage, which reduces file size while maintaining image legibility upon reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If image resolution is reduced to decrease file size, then storage and transfer costs are reduced, but text legibility deteriorates
Solution Approach 1:
The patent segments the image into tokens (groupings of pixels representing characters or symbols) and further segments similar tokens into classes. By storing only representative tokens from each class rather than all individual tokens, the file size is dramatically reduced while maintaining the ability to reconstruct legible text at high resolution.
Solution Approach 2:
The patent transforms the image representation from full-resolution pixel data to a parameter-based token system. Each token is represented by a small set of parameters (pixel coordinates, color values, and class identifiers) rather than storing complete pixel arrays, enabling compact storage while preserving visual quality upon reconstruction.
2Manufacturing precision
If manual correction is applied to fix OCR errors, then text accuracy is improved, but processing cost increases
Solution Approach 1:
The patent creates a simplified copy of the original image in token form, where each token captures the essential visual characteristics of text elements. This token-based representation serves as an intermediate layer that is easier to process and correct than full-resolution images, reducing the need for expensive manual correction while maintaining accuracy.
Solution Approach 2:
By converting images to token-based representations with discrete parameters, the system enables automated error detection and correction through parameter validation and consistency checks, reducing reliance on manual review and lowering processing costs.
3Manufacturing precision
If high resolution images are stored and transferred, then text legibility is maintained, but bandwidth requirements increase
Solution Approach 1:
The patent divides high-resolution images into discrete tokens that can be independently represented and transmitted. By grouping similar tokens into classes and storing only representative examples, the system maintains the visual quality needed for legibility while dramatically reducing the bandwidth required for transmission.
Solution Approach 2:
Instead of storing complete high-resolution images and then displaying them, the patent inverts the approach by storing simplified token representations and reconstructing high-resolution images only when needed for display. This reverses the traditional flow from storage to presentation, minimizing bandwidth usage during storage and transfer.
Data Source
AI summary
A token-based file may be compressed by applying a medial-axis transformation to the tokens in the file. This generates a topological skeleton of the token that is a thin version of the token, equal distant to its boundaries, i.e., a thinned token. Thinned tokens resulting from the medial-axis transformation are compared with each other and thinned tokens having substantial similar shapes are grouped together. Once the thinned tokens are classified into their respective groups, a representative token of each group is selected for storage along with an assigned token number and the position that each of the corresponding thinned tokens appeared in the work of content. The thinned token-based file may then be transferred to another computing device using less bandwidth than the original token-based file. A page image of the original work can then be reconstructed by the receiving computing device from the thinned token-based file.