The free online image to text tool reads the printed words in a photo, a screenshot or a scan and turns them into editable text, using Tesseract OCR in 100 plus languages. Because it runs in the browser, the image is never uploaded.
OCR and text recognition by OnlinePCApps since 2013
Text locked inside a picture cannot be copied, searched or edited. The free online image to text tool reads the words out with OCR and hands back plain text.
Copying a quote, a code snippet or an address out of a screenshot by hand is slow and error-prone. OCR reads the words in one pass, so the text is ready to paste rather than typed out line by line.
A scanned page is only a picture until the words are read out. OCR turns it into real text that can be searched, quoted and dropped into a document, which is the first step in digitising paper records.
An invoice, an ID or a contract read by OCR should not pass through an outside server. Tesseract runs in the browser, so the image stays on the device while the text is read from it.
Drag a photo, a screenshot or a scan onto the panel above. It can also be browsed to on the device. A clear, high-contrast image of printed text reads most accurately, and several images can go in together.
Choose the language of the text, or more than one for a mixed page. Tesseract reads the words on the device, showing a progress bar while the language data loads on the first run.
Read the text, fix any word the OCR misread, then copy it or download it as a .txt file. The original image stays untouched, so it can be read again in another language at any time.
To read an image is to recognise the printed characters and return them as text. The tool does that on the device.
The characters in a photo, a screenshot or a scan are recognised and returned as editable text. The engine reads printed type well, from a document font to a screenshot. It hands back words rather than a picture of them.
Tesseract recognises text in more than a hundred languages, from English and Spanish to Arabic, Chinese and Hindi. Two languages can be picked at once for a mixed page, such as a document with English and a second script.
The image is turned upright and cleaned before it is read, which lifts accuracy on a photo taken at an angle. A grayscale and contrast pass helps the engine separate the letters from the background.
The result is plain text to read, correct and reuse, kept as close to the layout of the page as OCR allows. It copies to the clipboard or saves as a .txt file, ready for a document, a note or a search.
To extract text from an image, to run OCR on a screenshot and to read a scan all name the same task. A search for image to text or OCR online reaches this tool, and the original image is left as it is.
OCR reads the printed characters and returns them as text. These points decide how the result lands.
| The case | Result | What happens and why |
|---|---|---|
| Printed text | strong | Clean, high-contrast print reads at about 95 percent or better on a clear image. |
| Handwriting | not supported | The engine is built for printed type, so handwriting reads poorly whatever the setting. |
| Languages | 100 plus | More than a hundred languages are read, and two can be picked at once for a mixed page. |
| Resolution | 200 DPI or more | Sharp, high-resolution text reads best, while a low-resolution scan drops accuracy. |
| Skew and rotation | auto-corrected | A tilted image is turned upright before reading, which recovers accuracy on a photo. |
| Multi-column | may reorder | A newspaper or a two-column page can be read across the columns instead of down. |
| Tables | text only | The words in a table are read, though the row and column structure is not kept. |
| Language data | downloads once | The data for a language is fetched once from a CDN, then cached for later runs. |
| Where it runs | on the device | The text is read in the browser, so the image is not uploaded. |
How OCR Reads an Image
Optical character recognition, or OCR, is the technology that reads the shapes of letters in an image and matches them to characters. This tool uses Tesseract, the open-source OCR engine that began at HP in 1985, was taken on by Google and was rebuilt in 2018 around neural networks for far better accuracy. It runs here through Tesseract.js, a WebAssembly build that reads the image on the device. One honest point sits at the centre of the privacy story: the image itself is never uploaded, while the data for a chosen language does download once from a CDN, a few megabytes that are then cached for later runs. Accuracy is the other honest point. Clean, high-contrast printed text reads at about 95 percent or better, yet the engine is built for print and not for handwriting, which reads poorly whatever the setting. A low-resolution scan, a photo in dim light, a heavy skew or a multi-column layout all pull accuracy down, so a quick read of the result before using it is wise. The references below define the engine and the format.
Both read text from an image. The trade is real, and a document is often confidential.
| Point of comparison | This tool Read in the browser On the device | Cloud OCR Uploaded and read on a server |
|---|---|---|
| Where the image goes | Stays on the device | Uploaded to a server |
| Price and caps | Free with no file cap | Free tier often capped |
| Read handwriting | Printed text only | AI models read cursive |
| Keep table structure | Text without the grid | Rows and columns kept |
| Thousands of pages | A set at a time in the browser | Server farms at scale |
Those last three rows favour a cloud service, since handwriting, a kept table structure and a run of thousands each call for more than a browser tab offers. For a screenshot or a clean scan the first two rows are what count. The image stays on the machine, and the reading is free with no per-page charge.
The image is read inside the browser by Tesseract compiled to WebAssembly, so the recognition is client-side and the file stays on the machine that opened it. The language data downloads once from a CDN, and no image is passed to a server for the job.
An image read by OCR is often a private thing, an invoice, an ID, a contract or a medical letter never meant for an outside server. A cloud OCR service has to upload the image to read it, far more exposure than pulling out some text is worth.
Each of these reads text from an image. They differ in effort, in cost and in where the file goes.
A phone, a cloud API and a desktop app all read text, yet each either suits a quick grab, uploads the image or has to be installed. This page runs the same Tesseract engine on a screenshot or a scan, kept local with nothing to set up.
A little context sets a sharp read.
Accuracy rises with a high-resolution, well-lit image where the text has strong contrast against the background. A blurry photo, a dim scan or tiny type all pull the reading down, so a sharp source is worth the effort.
Tesseract is built for printed type and reads it well, but it is not a handwriting recogniser and cursive comes out poorly. For handwritten notes a cloud service trained on handwriting is the better route.
Choosing the language of the text sharpens the reading, and two can be set at once for a mixed page. The data for a language downloads once on the first run, then is cached for every read after.
The browser reads an image or a small set in memory, which fits an everyday screenshot or scan. A folder of hundreds of pages, or scans that need heavy cleanup and deskewing first, belongs on the desktop edition, which reads from disk and processes the whole set in one pass.
Point it at a folder of scans and each one is read to its own text file in a single run, saved beside the source.
Deskew, denoise and threshold a batch of poor scans before reading, the preprocessing that lifts accuracy on hard pages.
Saved presets set the languages and the cleanup steps once, ready to apply across a repeated reading workflow.
Free and online, with no sign-up and no upload. Read the text from an image in the browser, all on the device.