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OCR Extract Text from Image

OCR Extract Text from Image

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View OCR Extract Text from Image Chrome Extension on Chrome Web Store
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Data is synced from the Chrome Web Store. View the official store page for the most current information.

Right click any image and extract its text instantly with offline OCR in a side panel.
Type
Extension
Users
20 users
1
Free Useful Apps
View author page of Free Useful Apps
Published
Published on May 31, 2025
Version 0.2.14
Manifest version
3
Updated
Updated on May 31, 2025
productivity/tools
Extension Category
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View OCR Extract Text from Image Chrome Extension on Chrome Web Store
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OCR Extract Text from Image Chrome Extension Image 1

Description

When you work on the web—researching, studying, coding, or simply sharing memes—you constantly bump into information trapped inside images. A screenshot of a zoom-call slide, a social-media infographic, the label on a product photo: each holds text you’d rather copy-paste than re-type.

After installation the extension registers a single context-menu entry that appears only when you right-click an image element. No clutter in normal menus, no toolbar buttons to remember—just “Extract text from image” exactly where you expect it. Click once and a Chrome side panel slides in, showing a friendly progress spinner followed by a textarea containing the recognised text. From that textarea you can:

Copy the full result with one click.

Real-World Use Cases Academic research – Copy inline citations or obscure symbols from scanned PDFs without launching a separate app.

Software development – Snag cryptic compiler errors shown in an embedded screenshot on Stack Overflow so you can search them directly.

Content creation – Extract quotes from Twitter images for alt-text or blog posts, preserving accessibility.

eCommerce & logistics – Pull serial numbers or SKU codes from product photos to paste into inventory software.

Language learning – Grab foreign words on a signpost photo and drop them into your flash-card deck.

In every scenario the side-panel model keeps the source page visible, so you can verify that the recognised text matches the image without juggling windows.

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