Document Fingerprinting via Text Block Layout Encoding
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Solution Overview
Problem
Traditional document management systems are resource-intensive and struggle with processing and storage demands due to large volumes of documents in various formats, especially when conducting searches or comparisons, which can be computationally expensive and inefficient on mobile devices.
Innovation Solution
A method for generating and utilizing document fingerprints using block encoding of text, allowing for quick comparison and search operations on devices with limited computing power by analyzing the layout of text in digital images, rather than the text content itself, enabling efficient document management and search functionalities on devices like smartphones and tablets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional optical character recognition techniques are used for document processing and search, then text extraction accuracy is improved, but computational cost and processing time increase significantly
Solution Approach 1:
The patent extracts only the essential layout features (text blocks, lines, and their spatial relationships) from documents, ignoring detailed character recognition. This extraction approach captures sufficient information for similarity search while avoiding the high computational cost of full OCR processing.
Solution Approach 2:
Instead of recognizing characters to understand document content, the patent inverts the approach by using layout patterns and spatial arrangements as the primary identification feature. This allows documents to be compared based on their structural fingerprint rather than semantic content.
2Measurement precision
If full-text comparisons are performed on mobile devices for document search, then search accuracy is improved, but device responsiveness deteriorates due to limited computing power
Solution Approach 1:
The patent segments documents into discrete layout elements (text blocks, lines) and represents each document as a sequence of these elements with their spatial relationships. This segmentation enables efficient comparison by focusing on structural patterns rather than processing entire text contents.
Solution Approach 2:
The patent changes the representation parameters from detailed text content to simplified layout features such as text block positions, line lengths, and spatial relationships. This parameter transformation reduces computational complexity while preserving essential document characteristics for accurate similarity search.
3Reliability
If multiple document versions and formats are stored in document management systems, then document retention compliance is improved, but storage requirements and processing complexity increase
Solution Approach 1:
The patent creates simplified layout fingerprint copies of documents that capture essential structural information. These compact representations serve as efficient proxies for full document storage, enabling compliance tracking with minimal storage overhead while maintaining the ability to identify and compare document versions.
Data Source
AI summary
Methods and apparatus for document encoding using block encoding of text are disclosed. A computing device is configured to detect, within a digitized image object, a plurality of element groups, where each group comprises one or more text image elements and is separated from other groups by at least one delimiter. The device generates a numerical representation of the groups, comprising a plurality of numerical values, where a particular value corresponding to a particular group is determined based at least in part on a combined size of text image elements of the particular group. The device stores at least a subset of the numerical representation as a fingerprint representing text contents of the digitized image object.