What resolution should I use for scanning documents for OCR?

300 DPI is the minimum for reliable OCR on printed text. 600 DPI is better for small fonts or detailed documents. Higher resolutions increase file size and processing time without significant accuracy gains above 600 DPI for most printed text.

Can I improve handwriting OCR accuracy with these tips?

Yes, especially tips 1 (higher resolution), 2 (higher contrast), and 3 (straighten the page). Tip 7 (crop to text area) helps when the handwriting is surrounded by blank space or a textured background.

Does reducing image file size hurt OCR accuracy?

Yes. File size reduction through compression (JPEG quality, image resizing) directly reduces the pixel information the OCR engine has to work with. For OCR, prioritize image quality over file size. Compress after OCR, not before.

Why does OCR work on the same document sometimes and fail other times?

Lighting conditions, camera angle, focus, and image processing applied by your phone or scanner can all vary between shots. Consistent conditions (same lighting, flat document, camera directly above) produce consistent results.

What is a good confidence score in FreeOCRKit?

FreeOCRKit shows a confidence percentage after extraction. Above 85% generally means good results for printed text. Below 60% usually means the image quality needs improvement. Handwriting OCR naturally produces lower confidence scores than printed text.

7 Ways to Improve OCR Accuracy — Get Better Results From Any Image

Why OCR Accuracy Varies So Much

OCR accuracy is not a fixed number. The same OCR engine can achieve 99% on a crisp business card scan and 40% on a blurry handwritten note photographed at an angle under bad lighting. The engine itself is constant — what changes is the input. Understanding which input factors matter most lets you fix the problem at the source rather than spending time cleaning up a bad result.

Tip 1: Increase Resolution to at Least 300 DPI

Low resolution is the most common cause of OCR failure. At 72 DPI (typical screen resolution), small characters blur into noise and the OCR engine cannot distinguish between similar letters. At 300 DPI or higher, individual character strokes are clearly separated. For scanning documents, always use 300 DPI or higher. For phone photos, move closer to the text to fill more of the frame with the content you need to extract.

Tip 2: Maximize Contrast Between Text and Background

Black text on white paper is the ideal OCR input. Low contrast — gray text on light gray paper, faded ink, colored text on a colored background — makes character boundaries ambiguous. If your image has low contrast, open it in any image editor (even the default Photos app on your phone) and increase brightness and contrast before uploading to FreeOCRKit.

Tip 3: Straighten Skewed or Rotated Pages

Skewed text (pages scanned at a slight angle) confuses OCR line-detection algorithms. Even a 5-degree rotation can reduce accuracy noticeably on multi-line documents. Most scanners have a de-skew option. For phone photos, keep the camera directly above the page and parallel to it rather than at an angle. Crop the image to just the text area before uploading.

Tip 4: Select the Correct Language

Tesseract.js uses language-specific character models. Running English OCR on a Spanish document works for most Latin characters but misses accented characters (é, ñ, ü) and may produce errors on common Spanish words. Always match the language selection to the document language. FreeOCRKit supports 20+ languages — extract English text here, Spanish text here, and French text here.

Tip 5: Remove Background Noise and Watermarks

Watermarks, stamps, stickers, sticky-note text, and background patterns all introduce noise that the OCR engine has to filter out. If your document has a large watermark overlaid on the main text, accuracy will drop. If possible, remove the watermark or crop around it before processing. For documents with light pattern backgrounds (legal letterhead, branded paper), the OCR engine usually handles it well unless the pattern is dense.

Tip 6: Use PNG Instead of JPEG for Screenshots

JPEG compression creates artifacts around sharp character edges — exactly the edges that OCR relies on. For screenshots and scanned documents, always save as PNG. PNG is lossless and preserves pixel-perfect character boundaries. If you only have a JPEG, increase the image size in an editor (upscaling adds pixels for the OCR engine to work with) before uploading.

Tip 7: Crop Out Non-Text Areas

Every element in the image that is not text — a photo, logo, diagram, margin space, or UI widget — adds noise that the OCR engine must classify and reject. Cropping the image to include only the text region reduces processing time and improves accuracy. For documents with mixed content (text alongside graphics), crop and OCR the text regions separately.