PDF Change Detection Using OCR and Segment Comparison
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Solution Overview
Problem
Conventional document management systems require manual and labor-intensive review processes to detect changes in documents, particularly when multimedia elements are involved, leading to potential human error and increased liability.
Innovation Solution
A document management system that utilizes image processing and machine learning to rasterize, segment, and compare original and modified PDF documents, identifying changes through optical character recognition and similarity analysis of text and multimedia elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual review processes are used to detect document changes, then users can identify modifications, but the process becomes time and labor intensive
Solution Approach 1:
The patent replaces manual mechanical review processes with an automated computer-based system that uses optical character recognition (OCR), image processing, and machine learning algorithms to detect document changes. The system rasterizes PDF documents, segments images, compares text representations, and identifies modifications automatically, eliminating the need for human reviewers to manually examine each document while maintaining high detection accuracy.
2Reliability
If manual review processes are used to detect document changes, then users can identify modifications, but the process requires increased labor
Solution Approach 1:
The system enables self-service change detection by automatically processing documents without requiring human intervention. The computer-based system performs all review functions independently - rasterizing documents, segmenting images, generating text representations through OCR, comparing segments between original and modified versions, and surfacing detected changes - thereby eliminating labor-intensive manual review while maintaining reliable change detection.
3Loss of time
If automated image processing is used to detect document changes, then review time is reduced, but the system complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the complex document comparison task into distinct modular stages: rasterization of PDF documents into images, segmentation of images into individual segments, generation of text representations through OCR for each segment, comparison of corresponding segments between original and modified documents, and surfacing of detected changes. This modular approach manages system complexity by breaking down the overall process into manageable, independent components that can be processed sequentially.
4Measurement precision
If comprehensive document analysis is performed to detect all changes, then detection accuracy improves, but processing time increases
Solution Approach 1:
The system performs comprehensive analysis only where necessary by segmenting documents into multiple parts and applying change detection algorithms selectively to each segment. Rather than processing entire documents as single units, the system analyzes individual segments independently, allowing for precise change detection in modified areas while avoiding unnecessary processing of unchanged portions, thereby balancing detection precision with processing efficiency.
Data Source
AI summary
A document management system surfaces changes to a portable document format (PDF) document to a user. The document management system converts each page of the PDF document into images, segments those images, and processes each segment of those images using computer vision and/or natural language processing. The document management system compares segments from an original copy of the PDF document with segments from a modified copy of the PDF document to identify significant changes to the PDF document.