Image to Text OCR

Extract text from images and screenshots using Tesseract.js OCR in the browser.

Tested tool guide Tested browser tools Checked August 16, 2026

What Image to Text OCR does and how it behaves

Use this to turn visible writing in a selected image into text that can be copied, searched, or edited. The tool performs optical character recognition in the browser with Tesseract.js, so the image is not uploaded for processing. It is most suitable for clear printed or screen-rendered text. A common surprise is that OCR produces an estimate, not an exact transcription: punctuation, spaces, character case, and reading order can be wrong even when the source looks readable to a person.

How the result is produced

Character recognition

The tool examines the image's pixels and returns the characters that Tesseract.js considers the most likely match. Recognition depends on visible letter shapes rather than embedded text metadata. A screenshot of selectable text is therefore treated like any other image. The result is extracted text, not a reconstruction of the original document, typeface, or visual formatting.

Image quality and processing

Clear, upright text with strong contrast generally provides the best source material. Blur, compression artifacts, shadows, patterned backgrounds, tiny lettering, and rotated lines can change the recognized characters. Processing occurs locally in the browser. Large or high-resolution images can require more time and memory, while aggressive downscaling can remove details needed to distinguish similar characters.

Good uses

Recover a paragraph from a screenshot when the original page or document is unavailable and its text cannot be selected.
Transcribe printed labels, notices, receipts, or scanned notes into text that can be searched and corrected.
Extract interface messages, serial numbers, or short codes from a screen capture without manually retyping every character.

Limits and checks

Compare names, dates, amounts, identifiers, and punctuation with the image. Similar shapes such as 0 and O, 1 and l, or 5 and S are common sources of consequential errors.
Do not assume that line breaks or reading order reproduce the source. Multiple columns, tables, sidebars, captions, and text placed at different angles can be merged or returned in an unexpected sequence.
Treat handwriting, decorative lettering, curved text, mathematical notation, and heavily degraded scans as uncertain. The presence of plausible-looking output does not establish that every character was recognized correctly.

Common questions

Can it read handwriting?

It may recognize occasional clear, print-like handwritten characters, but dependable handwriting transcription should not be assumed. Tesseract.js is better suited to machine-printed or screen-rendered text. Cursive writing, connected letters, inconsistent baselines, and personal letterforms can produce missing or substituted characters. Verify any handwritten result against the image and expect manual correction.

Will it preserve tables, columns, and formatting?

No, not as a faithful document conversion. OCR identifies text, while visual structure such as fonts, cell borders, indentation, and exact placement is not the same thing as textual content. Some line separation may be reflected in the result, but columns and tables can be read out of order. Rebuild important structure after checking the source image.

References and verification

The behavioral notes were checked against the browser implementation. Standards and primary references below define the relevant format, formula, or platform behavior.