OCR vs PDF to Text — Which Should You Use?

PDF text extraction and OCR solve the same problem — getting editable text from a PDF — but they work in completely different ways. Text extraction reads the character data already stored in a digital PDF, while OCR analyzes images of text and uses pattern recognition to identify letters and words. Choosing the right method depends on how your PDF was created, and PDFJolt offers both tools free in your browser.

The Fundamental Difference

To understand which tool you need, you first need to understand how PDFs store content. There are two fundamentally different types of PDFs, and they look identical on screen but are constructed entirely differently under the hood.

Digital PDFs (Text-Based)

A digital PDF is created by software — Microsoft Word, Google Docs, LaTeX, InDesign, or any application that "prints to PDF" or "exports as PDF." These PDFs contain actual text data: each character is stored with its font, size, position, and encoding. When you open a digital PDF and select text with your cursor, the text highlights word by word. You can copy and paste it.

For digital PDFs, text extraction is the right tool. The text is already there — you just need to pull it out.

Scanned PDFs (Image-Based)

A scanned PDF is created by a scanner, camera, or screenshot tool. Each page is stored as a raster image — a grid of pixels, like a photograph. The PDF viewer displays the image, and it looks like text to your eyes, but the PDF file contains no character data. When you try to select text in a scanned PDF, you typically select the entire page as a single image, or nothing at all.

For scanned PDFs, OCR is the only option. The text must be "recognized" from the image by analyzing letter shapes and patterns.

How to Tell Which Type You Have

The quickest test is simple: open the PDF and try to select a single word with your cursor (or long-press on mobile).

• If individual words highlight — You have a digital PDF. Use text extraction (PDF to Word).
• If the entire page highlights as one block, or nothing highlights — You have a scanned PDF. Use OCR.
• If some pages have selectable text and others do not — You have a mixed PDF. Some pages were digitally created and others were scanned. You may need to run OCR on the scanned pages and extract text from the digital pages separately.

Text Extraction: Fast, Accurate, Limited

How It Works

PDF text extraction reads the character data directly from the PDF's internal structure. Every character in a digital PDF is stored as a code point (e.g., Unicode) along with its font, size, and exact position on the page. Text extraction collects these characters, determines reading order based on position, groups them into words and paragraphs, and outputs clean text.

Advantages

• 100% accurate — The text is read directly, not interpreted. Every character is exactly correct.
• Extremely fast — Processing a 100-page PDF takes seconds.
• Preserves special characters — Accented letters, symbols, mathematical notation, and non-Latin scripts are read correctly if the font encoding is proper.
• Low resource usage — No heavy computation needed.

Limitations

• Only works on digital PDFs — If the PDF is a scan, there is no text data to extract.
• Reading order can be ambiguous — Multi-column layouts, text boxes, and complex page designs can make it difficult for the extractor to determine the correct reading sequence.
• Formatting is lost — Bold, italic, font changes, and visual structure are typically not preserved in the extracted text.

When to Use Text Extraction

Use text extraction (via PDFJolt's PDF to Word converter) when you have a PDF that was created digitally and you need to edit the content. This includes most PDFs received via email that were created in Word, Google Docs, or publishing software.

OCR: Powerful, Slower, Flexible

How It Works

Optical Character Recognition analyzes an image of text — whether from a scanned document, a photograph, or a screenshot — and identifies individual characters by comparing their shapes to known letter patterns. Modern OCR engines use machine learning models trained on millions of text samples to achieve high accuracy across fonts, sizes, and languages.

PDFJolt uses Tesseract.js, the WebAssembly port of Google's Tesseract OCR engine. Tesseract is the most widely used open-source OCR engine in the world, maintained by Google and supporting over 100 languages. PDFJolt runs Tesseract entirely in your browser — your scanned document never leaves your device.

Advantages

• Works on any document image — Scans, photos, screenshots, even PDFs with text baked into images.
• Supports 100+ languages — Including English, Spanish, French, German, Chinese (Simplified and Traditional), Japanese, Korean, Arabic, Hindi, Russian, and many more.
• Handles mixed content — Pages with both printed text and images (like textbook pages) can be processed.
• Creates searchable PDFs — OCR can add an invisible text layer on top of the scanned image, making the document searchable while preserving the original appearance.

Limitations

• Not 100% accurate — Even the best OCR engines make mistakes, especially with poor scan quality, unusual fonts, or handwritten text. Expect 95-99% accuracy on clean, printed documents.
• Slower processing — OCR requires significant computation. A 10-page scanned PDF may take 30-60 seconds to process, depending on your device.
• Quality dependent — Low-resolution scans (under 200 DPI), skewed pages, poor lighting, and faded text all reduce accuracy.
• Limited handwriting support — OCR engines are optimized for printed text. Handwriting recognition is unreliable.

When to Use OCR

Use PDFJolt's OCR tool when you have a scanned document, a photograph of text, or a PDF where you cannot select individual words. Common scenarios include digitizing paper documents, extracting text from scanned receipts or invoices, and making old documents searchable.

Side-by-Side Comparison

Feature	Text Extraction	OCR
Input type	Digital PDF	Scanned PDF, image, photo
Accuracy	100%	95-99% (varies)
Speed	Instant	30-60 seconds per page
Language support	All (font-dependent)	100+ languages
Handwriting	N/A	Limited
Scan quality dependency	None	High
Output format	Word, text	Searchable PDF, text
Processing location	Browser (PDFJolt)	Browser (PDFJolt)

Tips for Best OCR Results

• Scan at 300 DPI or higher. Higher resolution gives the OCR engine more pixel data to work with, improving character recognition accuracy.
• Ensure even lighting when photographing documents. Shadows across text significantly reduce accuracy.
• Keep pages straight. Skewed or rotated text is harder for OCR to process. Use PDFJolt's page tools to deskew if needed.
• Select the correct language before processing. OCR models are language-specific, and selecting the wrong language will produce poor results.
• Review the output. Even high-accuracy OCR can confuse similar characters: "l" and "1", "O" and "0", "rn" and "m". A quick review catches these common errors.

The Decision Flowchart

When you have a PDF and need to get editable text from it, follow this simple decision process:

1. Open the PDF and try to select text with your cursor.
2. If text selects word by word, use PDF to Word conversion for the fastest, most accurate result.
3. If text does not select (or selects as a full-page image), use OCR to recognize the text from the page images.
4. If you have a mixed document, process the scanned pages with OCR first, then merge everything together.

Both tools are free on PDFJolt and process entirely in your browser. Your documents never leave your device — whether you are extracting text from a digital PDF or running OCR on a scanned contract. Client-side processing means zero privacy risk, regardless of how sensitive the document is.