Extract text from an image

Clear, high-contrast printed text works best. Use a sharp source with enough pixels for small characters, even lighting, limited compression, and a page photographed as flat and straight as possible. Crop unrelated backgrounds and rotate the text upright before extraction. Very low resolution, motion blur, glare, shadows, textured paper, curved pages, decorative fonts, and aggressive image enhancement can merge or break character shapes. Enlarging a genuinely low-resolution source may help visibility, but it cannot recreate detail that was never captured.

The language choice determines which recognition model and character patterns are expected. Selecting English for Chinese, Japanese, Korean, Arabic, Vietnamese, or German text can produce plausible but incorrect substitutions because the expected alphabet, accents, direction, and word patterns differ. Choose the dominant language visible in the image. When one image mixes several languages, extract the most important section separately with its matching language and compare names, numbers, dates, and technical terms carefully because they receive less help from ordinary language patterns.

OCR identifies text regions and then orders them from their positions. Multi-column articles, tables, sidebars, forms, captions, vertical text, curved labels, overlapping stamps, and handwritten notes can make the intended sequence ambiguous. Crop independent regions and extract them separately when order matters. After extraction, compare the result with the source from top to bottom, restore paragraph breaks, and verify headings, table rows, labels, footnotes, and text that sits beside images rather than assuming a complete document layout was reconstructed.

No. This tool returns editable text and detected regions, not a Word, spreadsheet, or searchable PDF recreation of the original design. Columns can be read in an unexpected order, table cells can lose row and column relationships, and font, color, spacing, borders, images, and page furniture are not preserved as a matching layout. Use the result to avoid retyping, then rebuild required structure in the destination application and compare important values with the source before relying on them.

Time depends on image dimensions, number and size of text regions, layout complexity, selected language, rotation, and the resources required to prepare recognition. A large photograph with a small document in the center can require more work while still producing worse text than a tightly cropped scan. Use the smallest clear image that retains the needed characters, crop irrelevant areas, and avoid repeatedly enlarging already sharp sources. Keep the page open until a result or useful error appears.

Compare names, dates, addresses, totals, decimal separators, account numbers, identifiers, punctuation, and any character where a single mistake changes meaning. Common confusions include zero and O, one and lowercase l, similar punctuation, accented letters, and visually related characters in CJK or Arabic scripts. Review line order and missing text around images or tables. For legal, financial, medical, academic, or archival material, use a second review against the original image before copying the result into another record.