Document Conversion Correlation Engine for Markup Fidelity
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Solution Overview
Problem
The education publishing industry faces challenges in efficiently aggregating, transforming, distributing, and managing digital content due to a lack of digital textbook standardization, incompatible formats, content protection, and maintaining page fidelity during conversion to markup languages like HTML5, which hinders the growth of online delivery networks.
Innovation Solution
A document conversion correlation engine that analyzes the fidelity between printed documents and their HTML5 transformations, using algorithms like PCA and LDA to determine a correlation factor, ensuring page fidelity is preserved across various devices and browsers, and automatically flags pages that do not meet minimum fidelity thresholds for further correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If document pages are converted to markup language (HTML5) for digital publishing, then content can be delivered across multiple devices and platforms, but page fidelity between the original document and converted markup may be compromised
Solution Approach 1:
The system performs correlation analysis between source images and rendered markup images to generate feedback about page fidelity. This feedback loop allows the system to identify and correct conversion errors, ensuring that the markup language output maintains high fidelity to the original document while remaining compatible with multiple devices and platforms.
Solution Approach 2:
The patent replaces manual visual inspection and manual correction of converted pages with an automated computer-based correlation analysis system. The system uses algorithms to automatically compare source images with rendered markup images, identify discrepancies, and flag pages requiring correction, thereby maintaining precision at scale without manual intervention.
2Manufacturing precision
If manual inspection and correction of converted pages is performed, then page fidelity can be maintained, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system performs self-inspection through automated correlation analysis, comparing source images with rendered markup images without requiring manual intervention. The system automatically identifies pages that do not meet fidelity thresholds and flags them for correction, enabling the conversion process to maintain high precision while operating at automated speeds.
Solution Approach 2:
The patent replaces manual visual inspection and correction processes with an automated computer-based correlation analysis system. This substitution maintains page fidelity through algorithmic comparison while dramatically increasing conversion efficiency by processing multiple pages simultaneously without human intervention.
3Measurement precision
If various algorithms are used for correlation analysis, then measurement precision of page fidelity can be improved, but device complexity of the system increases
Solution Approach 1:
The system segments the correlation analysis into distinct algorithmic components: text comparison algorithms for textual content, image comparison algorithms for graphical elements, and statistical algorithms (PCA, LDA) for overall layout analysis. This segmentation allows each algorithm to specialize in specific aspects of page fidelity measurement, improving overall precision while maintaining manageable system complexity through modular design.
Data Source
AI summary
Embodiments of the disclosure provide a system for correlating document pages. The system receives a source image of a document page and a rendered image of a markup language page converted from the document page. The system then performs a correlation analysis between the source image and the rendered image. Next, the system determines a correlation factor between the source image and the rendered image based on the correlation analysis, wherein the correlation factor indicates a page fidelity between the document page and the markup language page converted from the document page.