Built on advanced on-device AI and hardware acceleration to deliver professional-grade performance with uncompromising privacy.On-device AI — professional-grade, fully private.
Image to Text
Extract Text from Images Instantly
- Text recognition text extraction · Copy or download as TXT
- 54 recognition languages · Batch (Pro)
- JPG, PNG, WebP, GIF
Drag & drop images
or click to browse · JPG, PNG, GIF, WebP, BMP
Note: First-time language loading may take a few seconds
Why use an Image to Text converter?
Text recognition lets you digitize printed content, extract text from screenshots and photos, and make visual text editable and searchable.
Benefits of text recognition technology
- Text extraction:: Extract text from photos, screenshots, and scanned pages.
- Document digitization:: Convert printed or scanned documents into editable text.
- Language coverage:: Recognize text in many major global languages.
- Privacy-first:: Recognized text is returned ready to copy or download.
- Faster workflows:: Reduce manual typing and speed up data entry.
How text recognition works
Text recognition analyzes image pixels, detects text regions, recognizes characters, and outputs machine-readable text.
Text recognition process
- Image preprocessing improves readability for recognition.
- Text detection identifies text-containing regions.
- Character recognition maps shapes to letters and symbols.
- Language processing improves interpretation accuracy.
- Text output is returned for copy, edit, or export.
How to extract text from images with text recognition
Upload images, select language, run text recognition, and copy or download extracted text.
- Upload image: Upload JPG, PNG, GIF, WEBP, or BMP files containing text.
- Select language: Choose the text language to improve recognition accuracy.
- Run extraction: Start text recognition and wait while the text is recognized.
- Copy or download: Copy extracted text or download it as a .txt file.
When to use text recognition
Use text recognition when you need editable text from non-editable image sources.
Ideal use cases
- Document capture:: Turn scanned pages into editable notes.
- Screenshot extraction:: Copy text from UI captures and image snippets.
- Data entry:: Extract rows of text before structured cleanup.
- Accessibility:: Make image text searchable and easier to process.
- Translation prep:: Extract source text for translation pipelines.
Quality considerations
Follow these guidelines to improve extraction quality and consistency.
- Use clear images with readable text and minimal blur.
- Ensure lighting is even and avoid glare on documents.
- Select the correct language before processing.
- Review extracted text and correct text recognition edge cases.
- For critical output, run a second pass with improved input quality.
When text recognition may not be ideal
- Very low-resolution or heavily compressed images.
- Extremely decorative fonts with low legibility.
- Dense layouts where reading order is critical without post-processing.
- Security-sensitive documents that must remain offline-only by policy.
Text recognition facts
These factors strongly influence text recognition quality.
Key quality factors
- Clear, high-resolution images usually produce better text recognition results.
- Good contrast between text and background improves recognition.
- Correct language selection reduces character substitution errors.
- Complex layouts can require manual review and cleanup.
- Handwriting may be less reliable than clean printed text.
Frequently asked questions
How do I improve text recognition accuracy for blurry or low-resolution images?
For best results, use images with at least 300 DPI and strong contrast between text and background. If your image is blurry, try sharpening it with an image editor before uploading. Cropping tightly around the text area also reduces noise and improves recognition accuracy.
Can I extract text from a scanned document or PDF screenshot?
Yes — screenshot any PDF page or scan a physical document, then upload the image here for text recognition extraction. Ensure the scan is straight, well-lit, and at a high resolution for best output. If you have an actual PDF file, a dedicated PDF to text tool will produce better results.
Which languages does this image to text converter support?
This text recognition tool supports over 100 languages, including Latin, Cyrillic, Arabic, Chinese, Japanese, and Korean scripts. Selecting the correct language before running extraction significantly improves accuracy, especially for non-Latin alphabets.
Why is my text recognition output showing garbled or incorrect characters?
Garbled output is usually caused by selecting the wrong language, poor contrast in the source image, or decorative and handwritten fonts that text recognition struggles to parse. Try re-running with the correct language selected, or enhance the contrast and brightness of the image before uploading.
Can I extract text from multiple images at once?
Yes, the tool supports batch processing so you can upload several images and extract text from all of them in a single session. Each image is processed separately, and you can copy or download each result individually — ideal for digitizing stacks of scanned pages.
How accurate is text recognition on handwritten notes compared to printed text?
Text recognition is significantly more accurate on clean printed text than on handwriting. Clear, block-style handwriting can yield usable results, but cursive script typically produces lower accuracy. Always review and manually correct the output when working with handwritten content.
from 436 ratings
Rate this tool
Tap a star — it takes a second