FOCUSED BROWSER-BASED TOOL
Turn printed text in images into editable text with private, browser-based OCR.
JPG, PNG, WebP, BMP, TIFF • up to 10 files, 20 MB each
Your images are processed locally in your browser and are not uploaded.
Image OCR guide
Optical character recognition examines pixels, estimates character shapes, and applies a selected language model. Add one or more images, select the language actually shown, optionally improve contrast or rotation, then review the editable output. OCR is an estimate, not a perfect transcription.
Use a straight, well-lit image with sharp printed text. Avoid glare, shadows, heavy JPEG artefacts, decorative fonts, and very small letters. Rotation corrects sideways pages; grayscale and contrast can separate text from its background. Threshold works best on clean documents and can remove faint details.
The tool supports JPG/JPEG, PNG, WebP, BMP, TIFF and TIF. Multipage TIFF files use only the first page. OCR languages are English, Hindi, Spanish, French, German, Italian and Portuguese; choose manually because automatic language detection is not implemented.
Image decoding, preprocessing and OCR run in your browser. The OCR engine downloads its code and selected language data when needed, but your image and extracted text are not sent to an OCR service or retained when you reset or close the page.
OCR can misread handwriting, curved pages, mixed languages, columns, tables, low-contrast scans, and stylised type. Basic line breaks can be kept, but visual document layout is not reproduced. Always proofread important text against the source image.
Create editable drafts from receipts, printed notes, screenshots, scanned documents, forms, book pages, product labels, classroom materials, and business cards. For best results, crop unrelated areas first and treat the output as a draft to verify rather than a guaranteed transcription.
OCR is fast and useful for producing a first draft from clear printed text. Manual transcription is slower but remains preferable when exact punctuation, complex formatting, handwriting, or high-stakes accuracy matters.
It uses optical character recognition (OCR) to estimate the printed characters visible in an image and turn them into editable text.
OCR analyses image shapes and uses a language model to estimate letters, words, and line breaks. The result can contain mistakes, especially in difficult images.
Yes. JPG and JPEG images are supported, along with PNG, WebP, BMP, TIFF, and TIF.
Yes. Add a PNG, select its text language, adjust preprocessing if needed, and choose Extract text.
Yes. Select Hindi before processing so the Hindi OCR language data is loaded.
It may recognise very clear handwriting, but this tool is intended primarily for printed text and does not promise reliable handwriting recognition.
Yes. Screenshots with large, sharp, high-contrast text usually give OCR more useful input.
Select the correct language, rotate the image, crop it first with Image Cropper, or try grayscale, contrast, threshold, invert, and enlargement controls.
No. This tool decodes, preprocesses, and recognises images in your browser. Files and extracted text are not sent to an OCR service.
Yes. Up to 10 supported images can be queued. They are processed one at a time to reduce browser memory pressure, and one failure does not stop later files.
Yes. Download edited results as UTF-8 TXT or structured JSON. For batches, download a ZIP containing both formats.
Blur, low resolution, unusual fonts, handwriting, complex layouts, compression, and the wrong language choice can all reduce OCR confidence.
The tool can preserve basic line breaks. It does not promise exact columns, tables, fonts, or page layout.
Yes, though OCR uses significant memory and processing power. Smaller, clear images work best on lower-memory devices.
Yes. Each file can be up to 20 MB, a batch up to 60 MB and 10 files, and each decoded image up to 40 million pixels.
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