How to Extract Text from Images Online (Screenshots, PDFs, Photos)

Step-by-Step: Extracting Text with ToolMasta

ToolMasta's Image to Text tool uses Tesseract.js — a WebAssembly version of Google's Tesseract OCR engine — running entirely in your browser. Here is the full process:

Step 1 — Open the OCR Tool

Go to the ToolMasta Image to Text (OCR) tool. No account is required. The tool works on desktop and mobile browsers.

Step 2 — Upload Your Image

Drag and drop your image onto the upload zone, or click to browse for a file. Supported formats include JPG, PNG, and BMP. If your image is a HEIC file from an iPhone, first convert it using the HEIC to JPG converter.

Step 3 — Select a Language

Choose the primary language of the text in your image. Selecting the correct language improves recognition accuracy because the engine uses language-specific models and dictionaries. English is selected by default.

Step 4 — Extract Text

Click Extract Text. Tesseract processes the image locally and displays the recognised text in a text area below. The processing time depends on image size and complexity — typically two to ten seconds.

Step 5 — Copy and Use

Select all the extracted text (Ctrl+A or Cmd+A in the text box) and copy it. Paste it into any application — a word processor, spreadsheet, email, or note.

Extracting Text from Screenshots

Screenshots are among the most common inputs for OCR. You might want to extract text from:

• An error message you cannot copy because it appears in a dialog box
• A website that has disabled text selection
• A presentation slide you received as an image
• A social media post you want to quote in writing

Screenshots are ideal for OCR because they are always at screen resolution (96–144 dpi on modern displays), have perfect contrast (digital text rendering), and are never blurry. The main challenge is that screen text is often very small, which can reduce accuracy for standard OCR engines. If you are extracting from a screenshot, zoom into the text before screenshotting to increase the effective resolution. On Windows, use Win+Shift+S to take a region screenshot at full scale.

Keyboard Shortcuts for Screenshots

• Windows: Win+Shift+S (region screenshot to clipboard), PrtScn (full screen)
• Mac: Cmd+Shift+4 (region screenshot), Cmd+Shift+3 (full screen)
• iPhone: Power + Volume Up simultaneously
• Android: Power + Volume Down simultaneously (varies by device)

Getting Good Results from Phone Photos

Photos taken with a phone camera are more challenging for OCR than screenshots because they introduce real-world imperfections: blur, lighting variation, shadows, and perspective distortion. Here are the key tips for maximising accuracy:

Lighting

Photograph documents in bright, even lighting — ideally natural daylight without direct sun. Avoid shadows falling across the text. Overhead fluorescent light is fine for indoor photography. Avoid using flash directly, as it creates glare on glossy paper.

Camera Position

Hold the camera directly above and parallel to the document. Even a slight angle introduces perspective distortion that makes text harder to recognise. Most modern phone cameras have a built-in level indicator — use it. Many scanning apps apply perspective correction automatically, but less distortion at source is always better.

Focus and Stability

Tap on the text area to focus. Blurry text dramatically reduces OCR accuracy. If your phone does not hold focus well for close shots, try propping the phone or using a tripod. Take several shots and use the sharpest one.

Use a Scanning App

For multi-page documents, consider using your phone's built-in scanning function (Notes on iPhone, Google Drive on Android) which applies perspective correction, enhances contrast, and saves at a good resolution. Save the output as a JPG and feed it to ToolMasta's OCR tool.

Extracting Text from PDF Pages

PDF files come in two types: those with a text layer (searchable PDFs) and those without (image-based or "scanned" PDFs). Before using OCR, determine which type you have:

• Searchable PDF: Open the file in your PDF reader and try to select text with your mouse. If text highlights, the PDF already has a text layer — you can copy text directly without OCR.
• Image-based PDF: If you cannot select text, the PDF contains scanned images. You need OCR to extract the text.

For image-based PDFs, the workflow with ToolMasta is:

1. Use the PDF to Images tool to convert each page to a JPG or PNG
2. Upload each page image to the OCR tool and extract the text
3. Combine the extracted text from each page in a text editor

Troubleshooting Poor OCR Results

If the extracted text contains many errors, here are the most effective fixes:

Problem	Likely Cause	Solution
Garbled characters everywhere	Wrong language selected	Change the language setting to match the document
Occasional wrong characters	Similar-looking letters (l/1, O/0)	Increase image resolution; normal for most tools
Text blocks merged together	Layout complexity or low contrast	Crop and process one column at a time
Blank output	Image is too small or too dark	Brighten/resize the image before uploading
Poor results on all text	Blurry image or low DPI	Rescan/re-photograph at higher quality