Question 1

How does the PDF Text Extractor work?

Accepted Answer

It parses each PDF page's content stream in your browser and pulls out embedded text from text-showing operators (Tj, TJ, ', "). If the PDF only contains scanned images (no embedded text layer), the tool reports the page as empty and explains that real OCR would require a heavy dependency like Tesseract.js.

Question 2

What output formats are supported?

Accepted Answer

Four formats: plain text (one section per page), JSON (page → text mapping), CSV (one row per page: page, charCount, wordCount, text), and Markdown (with page headings and fenced blocks).

Question 3

What extra features does this tool have compared to others?

Accepted Answer

(1) Page-range parser (1-3, 5, 8-). (2) Four output formats (text/JSON/CSV/MD). (3) Page-number headers. (4) Line-break preserver. (5) Text statistics (chars/words/lines/paragraphs). (6) Page separator generator. (7) Empty-page detector. (8) Text quality scorer. (9) Multi-format renderers. (10) Copy + download. (11) History (localStorage, last 20). (12) Shareable URL. (13) Summary stats (pages, extracted chars, avg/page). (14) In-content text search. (15) Keyword frequency analyzer (top 20). (16) Reading-time estimator. (17) Basic language detector. (18) Empty-page filter.

Question 4

Why can't I get text from a scanned PDF?

Accepted Answer

Scanned PDFs store only raster images — there is no text layer to extract. True OCR (recognizing characters in images) needs a large (~10 MB+) ML model such as Tesseract.js. This tool focuses on instant, private extraction of the embedded text layer. For scanned documents, you'll see 'no embedded text' notes per page.

Question 5

Is my data sent anywhere?

Accepted Answer

No. PDF parsing, text extraction, formatting, statistics, and downloads all run locally in your browser. No file or extracted text is ever uploaded. History is stored in your own localStorage.

PDF Text Extractor

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