I have been trying to write a simple console application or PowerShell script to extract the text from a large number of PDF documents. There are several libraries and CLI tools that offer to do this, but it turns out that none are able to reliably identify document structure. In particular I am concerned with the recognition of text columns. Even the very expensive PDFLib TET tool frequently jumbles the content of two adjacent columns of text.
It is frequently noted that the PDF format does not have any concept of columns, or even words. Several answers to similar questions on SO mention this. The problem is so great that it even warrants academic research. This journal article notes:
All data objects in a PDF file are represented in a visually-oriented way, as a sequence of operators which...generally do not convey information about higher level text units such as tokens, lines, or columns—information about boundaries between such units is only available implicitly through whitespace
Hence, all extraction tools I have tried (iTextSharp, PDFLib TET, and Python PDFMiner) have failed to recognize text column boundaries. Of these tools, PDFLib TET performs best.
However, SumatraPDF, the very lightweight and open source PDF Reader, and many others like it can identify columns and text areas perfectly. If I open a document in one of these applications, select all the text on a page (or even the entire document with CTRL+A) copy and paste it into a text file, the text is rendered in the correct order almost flawlessly. It occasionally mixes the footer and header text into one of the columns.
So my question is, how can these applications do what is seemingly so difficult (even for the expensive tools like PDFLib)?
EDIT 31 March 2014: For what it's worth I have found that PDFBox is much better at text extraction than iTextSharp (notwithstanding a bespoke Strategy implementation) and PDFLib TET is slightly better than PDFBox, but it's quite expensive. Python PDFMiner is hopeless. The best results I have seen come from Google. One can upload PDFs (2GB at a time) to Google Drive and then download them as text. This is what I am doing. I have written a small utility that splits my PDFs into 10 page files (Google will only convert the first 10 pages) and then stitches them back together once downloaded.
EDIT 7 April 2014. Cancel my last. The best extraction is achieved by MS Word. And this can be automated in Acrobat Pro (Tools > Action Wizard > Create New Action). Word to text can be automated using the .NET OpenXml library. Here is a class that will do the extraction (docx to txt) very neatly. My initial testing finds that the MS Word conversion is considerably more accurate with regard to document structure, but this is not so important once converted to plain text.