What is the Image Text Extractor?
The Image Text Extractor is a powerful tool that uses Optical Character Recognition (OCR) technology to detect and extract text from images. This is especially useful when you need to work with text that's embedded in screenshots, scanned documents, or photographs.
Step-by-Step Guide
- Upload Your Image: Click on the upload area or drag and drop an image file. Supported formats include JPG, PNG, GIF, and BMP.
- Preview the Image: After uploading, you'll see a preview of your image and an empty text area where the extracted text will appear.
- Extract Text: Click the "Extract Text" button to begin the OCR process. The tool will analyze the image and convert any detected text into editable format.
- Monitor Progress: During extraction, you can monitor the progress through the progress bar and status updates.
- Review Results: Once extraction is complete, the text will appear in the text area. You can review and edit it if needed.
- Copy or Download: Use the "Copy Text" button to copy the extracted text to your clipboard, or the "Download Text" button to save it as a text file.
- Clear and Start Over: If you need to process a new image, use the "Clear Data" button to reset the tool.
Tips for Best Results
- Use high-quality images with clear, legible text for best accuracy
- Ensure good contrast between text and background
- Avoid images with heavy shadows, glare, or distortion
- For scanned documents, use at least 300 DPI resolution
- Crop the image to focus on the text area if possible
- The tool works best with printed text rather than handwriting
Common Use Cases
The Image Text Extractor is useful for:
- Digitizing printed documents or books
- Extracting text from screenshots
- Converting scanned PDFs to editable text
- Reading text from product labels or packaging
- Translating text from images in foreign languages
- Archiving information from photographs of signs or documents
About the Technology
This tool uses Tesseract.js, an open-source OCR engine that supports multiple languages and can recognize text in various fonts and formats. While OCR technology has improved significantly, it may not be 100% accurate, especially with poor quality images or unusual fonts.