Document Annotation Removal via Digital Component Parsing
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Solution Overview
Problem
Existing methods for restoring modified documents to their original state, whether physical or digital, are inefficient and often cannot completely remove annotations, especially when original text or graphics are highlighted in contrasting colors.
Innovation Solution
The technique involves scanning or digitizing modified documents, categorizing content into structured and unstructured components, and using a parser to separate original content from annotations, allowing for the generation of a digital copy that replicates the original document by excluding added markings, which can be displayed or printed separately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual erasing or masking techniques are used to restore physical documents, then some annotations can be removed, but the process is manually intensive and cannot completely remove all annotations
Solution Approach 1:
The patent replaces manual mechanical erasing/masking operations with an automated optical-digital system. An optical scanner captures the document image, and software algorithms automatically detect, classify, and separate annotations from original content, eliminating the need for manual intervention while achieving complete annotation removal.
Solution Approach 2:
The patent creates a digital copy of the physical document through optical scanning, then performs restoration operations on the digital copy rather than the physical original. This allows complete annotation removal in the digital version while preserving the physical document, achieving both efficiency and completeness.
2Object-generated harmful factors
If correction fluid is used to mask handwritten notations, then some markings can be hidden, but original text or graphics highlighted in contrasting colors cannot be masked
Solution Approach 1:
The patent replaces physical masking materials like correction fluid with digital image processing techniques. The system uses optical scanning followed by software-based annotation detection and removal, which can handle all types of markings including contrasting color highlights without the limitations of physical masking materials.
Solution Approach 2:
The patent changes the state of the document from physical to digital format, enabling flexible manipulation of visual parameters. By converting to digital form, the system can selectively adjust parameters like color thresholds, contrast levels, and detection sensitivity to remove various types of annotations that would be impossible to mask physically.
3Reliability
If physical documents are manually restored, then time-consuming manual intervention is required, but complete annotation removal is achieved
Solution Approach 1:
The patent replaces time-consuming manual restoration operations with automated optical scanning and software processing. The system rapidly captures document images and uses algorithms to automatically detect, classify, and remove annotations, achieving complete restoration in a fraction of the time required for manual processes.
Solution Approach 2:
The patent performs restoration on a digital copy rather than the physical original, enabling rapid processing without affecting the physical document. Multiple operations can be performed on the digital copy simultaneously, significantly reducing restoration time while maintaining complete annotation removal.
Data Source
AI summary
Techniques are disclosed for restoring a modified document to an original state. The modified document is scanned into a digital form using an optical scanning device. The content of the modified digital document including one or more annotations is then grouped into several components, including text, images, form fields and text boxes, and marked shapes, based on corresponding component specifications. Each component is then categorized as being structured or unstructured. Structured components that correspond with representative entries in a component repository, such as text in a standard font size, weight and style, are identified as core document content. Unstructured components are identified as annotated document content or highlighted document content, depending on certain characteristics of the components. The categorized and identified components can then be presented separately or in various combinations.