PDF Text Layer Extraction via Metadata Analysis
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Solution Overview
Problem
Existing methods for extracting data from PDF documents are inefficient, particularly for true PDF pages, where content is inaccessible, and for searchable PDF pages, where OCR tools may not provide reliable results.
Innovation Solution
A system and method that analyze the metadata of a text layer in a PDF document to identify true PDF documents, allowing for the extraction of data without using optical character recognition (OCR), by creating a template with coordinates corresponding to selected fields and extracting data based on this template from accessible text layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If OCR tools are used to extract content from searchable PDF pages, then data extraction is possible, but reliability is poor
Solution Approach 1:
The patent extracts the text layer from the PDF document structure and separates it from the need for OCR processing. By directly accessing the embedded text content in searchable PDFs through programmatic extraction of the text layer, the system eliminates reliance on OCR tools while maintaining high extraction speed.
Solution Approach 2:
The patent introduces an intermediary text layer extraction mechanism that sits between the PDF document and the final output. This text layer acts as a mediator that provides reliable, structured text data without requiring OCR processing, thus improving both reliability and maintaining productivity.
2Measurement precision
If metadata analysis is performed to identify true PDF documents, then extraction accuracy is improved, but processing time increases
Solution Approach 1:
The patent performs preliminary metadata analysis when the PDF document is first loaded or registered in the system. By identifying the PDF type (true PDF, searchable PDF, or image-only PDF) in advance through metadata examination, the system prepares the appropriate extraction strategy beforehand, eliminating the need for repeated analysis during actual data extraction operations.
Solution Approach 2:
The patent changes the parameter of PDF document classification by analyzing specific metadata parameters (such as the presence of text layers, OCR flags, and document structure) to automatically categorize documents. This parameter-based classification enables rapid identification of PDF types without time-consuming manual inspection.
Data Source
AI summary
The system may perform a method comprising analyzing metadata of a text layer of a page of a first pdf document to determine that the pdf document is a first true pdf document; receiving the first true pdf document, in response to the first pdf document being the first true pdf document; receiving a selection of a field including first data to be extracted from the first true pdf document; displaying the first data; creating a template including the coordinates corresponding to the selected field and the first data of the first true pdf document; and extracting from an accessible text layer of a second true pdf document, second data based on the template from the first true pdf document.