In this post, I will show you 5 free methods to extract text from images you see on the web or on your local storage. You can easily copy text from pictures on your Windows PC, Mac, iPhone, or Android phone. 

Highlight or Copy Text While Browsing the Web

While browsing the web, you may find texts on comics, posters, charts, screenshots, memes, etc. You may want to interact with these texts shackled to images. For instance, copy or translate the text on images. 

In that case, you can get this Chrome extension, Project Naptha. Once you get this extension installed, you can highlight any text on images while browsing the web. Right-click and you can select Copy Text, Translate, etc. 

The available language for translation including English, Spanish, Russian, Chinese Simplified, Chinese Traditional, Japanese, German, and French. For coping English text, you can also right click on the selection to change the OCR engine to “Tesseract” under the “Language” menu.  

Extract Text from Image Online

There are a few free online OCR services that allow you to extract text from pictures. You just need to upload your image and then the text is ready to be copied. I will take the Text Extractor Tool by Brandfolder as an example to show you how it works. 

Step 1. Go to the tool web page.

Step 2. Click on the “+” icon to upload your image or simply drag it here. You can also select image files from cloud drives. 

Step 3. In a few seconds, your text will be extracted in the box below. You can click the Copy Text button to copy the extracted text. 

OCR apps for Android and iOS

Microsoft has released a free OCR app, Office Lens, for iOS and Android. It allows you to take a photo or select one from your photo library to extract text. You may trim or optimize the image to make the result more accurate. 

Step 1. Free download Microsoft Lens from AppStore or Play Store. With Lens app, slide left to lock on ACTIONS on the bottom. 

Step 2. Based on your needs, you can tap on TEXT, TABLE, or READ. TEXT is for extracting text, TABLE for extracting tables, Read is for reading the text on the image.

Step 3. Capture an image or tap on the Photo icon at the left bottom to select an image from the Photos app. 

Step 4. Select the text to extract and press Confirm. 

Step 5. In a few seconds, you will see the extracted text. You can now copy the text or share it. 

Lens also allows you to scan documents and there are many languages that you can choose. If you also have other office apps from Microsoft, then Microsoft Lens is definitely good for you. If you prefer Google apps, then you can use Google Lens, Google Keep, or Google Photos to extract text from images. 

Copy Text from Image on Windows or MacOS

If you want to extract text from pictures on your computer, then I recommend the OneNote app. It is a great note app from Microsoft and you probably already have installed it. It allows you to copy text from the images of a multiple-page file printout.

Step 1. Add the pictures from which you want to extract text to OneNote app.

Step 2. Right-click the picture, and click Copy Text from Picture.
Step 3. Click where you’d like to paste the extracted text, and then press Ctrl+V.

OCR Shortcut for iOS

For iOS users, you don’t even need additional apps for this. In iOS 15 or iPadOS 15, the Shortcuts app offers the action, Extract Text from Image. You can refer the video below to create a shortcut for extracting text from images step by step.

If your iPhone is running iOS 14 or previous versions, you can choose a few shared OCR shortcuts for this purpose. I recommend Rob’s OCR. You can open this link in Safari to get it. If you have a problem importing this shortcut, you can read this post to get started with Shortcuts

This shortcut relies on third-party OCR service, so you need to get a free personal API key from OCR.Space for this shortcut to work. When you run it for the first time, this shortcut will guide you through the process. .

Conclusion

Based on the device you use, you can choose one of the methods to extract text from image. Whether you want to recognize text on the web or anywhere you see, you can find at least one working method here. Now, it is your trun. Which of these method do you like the most? 

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