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Non-OCR Table Extraction from PDF Documents
PDF documents often contain tables, which are essential data structures for many applications. However, extracting tables from PDFs as structured data remains a challenge, especially when OCR is not an option.
The Limitations of PDF Rendering
Many attempts to extract tables start by converting PDFs to HTML. However, this approach often yields unsatisfactory results, especially with non-English documents, due to font issues and poor text recognition. Alternatively, extracting tables based on x and y coordinates is not feasible for documents with varying table positions.
The Complexity of Human Table Recognition
The fundamental difficulty lies in the fact that PDFs do not explicitly define table structures. Instead, they render text and lines that humans interpret as tables. To replicate this interpretation in code is an arduous task.
Non-Extractable Text
In the specific example provided, an additional issue arises: the document contains corrupted text data, making direct text extraction impossible. Copying and pasting the text from Adobe Reader does not produce meaningful results, hampering the feasibility of text-based extraction methods.
Conclusion
While simple text extraction from PDFs is relatively straightforward, reliable table extraction as structured data remains a challenge, especially when OCR is not an option. The limitations of PDF rendering, the complexity of human table recognition, and potential text corruption issues present significant obstacles to automated table extraction. As a result, customized solutions tailored to specific document structures and formats are often necessary to extract tables from PDFs effectively.
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