OCR Accuracy: How to Get Better Text Extraction Results

OCR technology is impressive, but it's not perfect. Sometimes it confuses "rn" with "m", reads "5" as "S", or turns tables into gibberish. The good news: many OCR errors come from poor input quality, not poor OCR software. Improve the input, and you'll dramatically improve the output. In our testing, the same document scanned at 150 DPI versus 300 DPI can mean the difference between 82% and 98% accuracy.

Here are proven techniques to get the best OCR accuracy possible, based on years of processing millions of documents.

The #1 Factor: Scan Quality

OCR accuracy starts with the quality of the source image. A clean, high-resolution scan will always produce better results than a blurry photo. This is the single most important factor you can control.

  • Resolution — Scan at 300 DPI minimum. 600 DPI is better for small text (under 8pt) or detailed documents. Going above 600 DPI rarely improves results and increases file size unnecessarily.
  • Color depth — Even for black-and-white documents, scan in color or grayscale. This preserves subtle details like faint text and light pencil marks that help OCR.
  • Flat and straight — Press pages flat against the scanner glass. Curved or skewed pages cause character distortion that no software can fully correct.
  • Clean glass — Wipe the scanner glass before each batch. Dust and fingerprints create noise that the OCR engine may interpret as characters.
  • Consistent lighting — If using a camera instead of a scanner, ensure even lighting without shadows. Shadows across text can cause entire words to be misread.

Image Preprocessing Tips

If you're working with existing images or photos of documents, preprocessing can significantly improve OCR results:

  • Increase contrast — Make the text as dark as possible and the background as white as possible. This single step can improve accuracy by 10-15%. Most image editors (even phone photo editors) can do this.
  • Remove noise — Clean up speckles, shadows, and artifacts. Scanner dust creates small dots that OCR may interpret as periods or commas.
  • Deskew — Straighten rotated or tilted pages. Even a 2-degree tilt can reduce accuracy by 5-10%. Most scanner software has auto-deskew, or use a free image editor.
  • Crop margins — Remove unnecessary borders that can confuse the OCR engine about where the text begins and ends.
  • Sharpen — A slight sharpen can help blurry characters become distinct. Don't over-sharpen, though — this creates artifacts that are worse than the original blur.
  • Convert to black and white — For text-only documents, converting to pure black and white (threshold) removes color noise and makes text stand out clearly.

Choose the Right Language

OCR engines use language models to improve recognition. Selecting the wrong language is one of the biggest causes of poor accuracy — it's like asking the OCR to read English text using a Chinese character set:

  • English document? Set OCR language to English
  • Mixed English and Spanish? Select both languages
  • Document with numbers and codes? Make sure the OCR supports numeric recognition
  • Document with accented characters (é, ñ, ü)? Select the language that includes those diacritical marks

If you're unsure which language to select, check the document for clues: letter patterns, common words, and character types. When in doubt, selecting the correct language plus English often helps because many documents contain occasional English words.

Font Considerations

Not all fonts are equally easy for OCR to read:

  • Best — Clean sans-serif fonts like Arial, Helvetica, Calibri. These have distinct character shapes with clear separation.
  • Good — Standard serif fonts like Times New Roman, Georgia. Slightly harder due to decorative strokes, but still very recognizable.
  • Moderate — Decorative or stylized fonts. Unusual letter shapes increase confusion.
  • Difficult — Handwritten text, typewriter text, dot-matrix print. These vary too much from the standard character patterns OCR engines are trained on.

Layout Complexity

Simple layouts OCR better than complex ones. The OCR engine needs to determine reading order and text boundaries:

  • Single-column text is easiest for OCR — the engine reads top to bottom, left to right
  • Multi-column layouts can cause text from different columns to merge, creating garbled output
  • Tables with clear borders work well; borderless tables may confuse the OCR about cell boundaries
  • Headers, footers, and sidebars can be excluded from OCR if they're not needed
  • Text wrapping around images is difficult — the engine may lose the reading flow

Common OCR Errors and How to Fix Them

  • "rn" → "m" — Characters too close together. Increase scan resolution or try slight sharpening.
  • "cl" → "d" — Similar issue with adjacent characters merging. Better preprocessing helps.
  • "0" vs "O" vs "D" — Context-dependent confusion. Correct language selection helps the OCR choose based on word patterns.
  • "1" vs "l" vs "I" — Same issue. Monospace fonts reduce this confusion. Language context helps.
  • Broken characters — Low resolution or dirty scanner glass causes gaps in characters. Clean the glass and increase DPI.
  • Missing diacritical marks — Accents and umlauts are often missed. Ensure the correct language is selected.
  • Merged lines — When lines of text are too close together, OCR may read two lines as one. Increase scan resolution.

Post-OCR Quality Improvement

Even with the best settings, plan for some post-processing:

  • Use spell check — Paste OCR output into a word processor and run spell check. This catches most character-level errors.
  • Search and replace common errors — OCR tends to make the same mistakes repeatedly. If "rn" was read as "m" once, it probably happened throughout the document.
  • Verify numbers manually — Numbers are critical and OCR errors in numbers can have serious consequences. Check every phone number, date, and financial figure.
  • Review tables separately — Tables are the hardest element for OCR. Rebuild complex tables manually if needed.

Frequently Asked Questions

What resolution should I scan at for OCR?

300 DPI is the standard for OCR. For very small text (under 8pt), use 600 DPI. Going above 600 DPI rarely improves results and increases file size. Below 150 DPI, accuracy drops significantly.

Can OCR handle poor-quality photocopies?

OCR can work on photocopies, but accuracy drops with each generation of copying. If possible, scan the original document rather than a copy. Each photocopy generation loses about 5-10% accuracy.

Does image format matter for OCR?

Yes. Use lossless formats like PNG or TIFF for the best OCR input. JPEG compression introduces artifacts (small blocks and blurring) that can confuse the OCR engine. If you only have JPEG images, use the highest quality setting.

How can I improve OCR on old documents?

Old documents present challenges like faded ink, yellowed paper, and stains. Increase contrast aggressively, convert to black and white, and scan at 600 DPI to capture as much detail as possible. See our guide on handling poor quality scans.

Summary

Better OCR results start with better input. Scan at 300+ DPI, use clean and straight pages, select the correct language, and preprocess images for contrast. The PDF OCR tool uses advanced recognition technology — give it quality input and you'll get 95-99% accuracy on most documents.