Extract On-Screen Text from Video Online
Use OCR to recognize text in video frames—hardcoded subtitles, titles, danmaku, presentation text—automatically generating text with a timeline, one-click export to TXT and SRT, all processed locally in your browser
OCR on-screen text recognition
Reads the video frame by frame to recognize burned-in text—hardcoded subtitles, titles, danmaku and watermark text—complementing audio-based speech recognition
Selectable area + custom interval
Recognize only the bottom subtitle area for higher accuracy, with a flexible sampling interval that balances speed and completeness; results are automatically deduplicated and merged
Local processing protects your privacy
Frame decoding and text recognition both run locally in your browser; videos are never uploaded to any server, so even private content is safe
Drag and drop video files here
or
Supports MP4, WebM, MOV, MKV, AVI, and more
Use cases for extracting on-screen video text
Content organization & learning
- Extract text from PPT/whiteboards in course and lecture recordings and organize it into searchable notes
- Extract text from videos with hardcoded subtitles (subtitles burned into the frame) to create transcripts or study materials
- Extract code, commands and step-by-step text shown on screen in tutorial and demo videos
Creation & office
- Extract titles, danmaku and sticker text from short videos for repurposing and analysis
- Recover an editable SRT from videos that only have hardcoded subtitles and no separate subtitle file
- Extract key information and data from slides in product demos and launch recordings
How to Use
Upload Video
Click the upload area or drag and drop a video file. Supports MP4, MKV, WebM, MOV, and more.
Choose language and recognition area
Choose the language of the on-screen text, and select the entire frame or bottom subtitle area only as needed
Start recognition
Click “Start Text Recognition” and OCR recognizes on-screen text frame by frame locally
Preview & export
Preview the results, download TXT/SRT or copy the plain text with one click
About the on-screen video text extractor
VideoKit’s on-screen video text extractor is built on WebCodecs and local OCR (optical character recognition): it first decodes the video frame by frame into images, then recognizes the text appearing in each frame, automatically deduplicating and merging it into text with a timeline.
It is designed to recognize text “burned into the frame,” such as hardcoded subtitles, titles, danmaku, watermarks and text on presentation screens. If you want subtitles transcribed from audio, please use the “Extract Video Subtitles” (speech recognition) tool.
All processing runs locally in your browser; the video and recognized text never leave your device. Chrome or Edge is recommended; OCR quality depends on the clarity, size and contrast of the on-screen text, so proofreading after export is recommended.
Frequently Asked Questions
How is this different from “Extract Video Subtitles”?
This tool uses OCR (optical character recognition) to “look” at the video frame by frame and recognize text burned into the picture—such as hardcoded subtitles, titles, danmaku, watermark text, and words on PPT/presentation screens. The “Extract Video Subtitles” tool instead uses speech recognition (ASR) to “transcribe” what is said. In short: use this tool for text on the screen, and the subtitle tool for spoken audio.
How does it recognize on-screen text?
Based on the sampling interval you set, the tool captures the video frame by frame into images, then uses a local in-browser OCR engine to recognize the text in each frame, and finally deduplicates and merges the results into text segments with a timeline. The whole process runs in your browser and the video is never uploaded.
Which text languages are supported?
Supported languages include Chinese (Simplified/Traditional), English, Japanese, Korean, French, German, Spanish, Portuguese, Italian, Russian, Arabic, Hindi, Vietnamese, Turkish, Indonesian and more. Choose the language matching the on-screen text before recognition; for mixed Chinese and English, pick the “Chinese + English” option for better results.
How do I choose the sampling interval and recognition area?
A smaller interval yields more complete results but frame-by-frame OCR is slower, so for long videos try a 2–5 second interval first. If the text is concentrated at the bottom of the frame (typical hardcoded subtitles), setting the recognition area to “Bottom subtitle area only” filters out other distractions, speeds things up and improves accuracy; otherwise use “Entire frame”.
Will my video files be uploaded to a server?
No. Video decoding, frame capture and OCR text recognition all run locally in your browser; the video file is never uploaded to any server. The recognition engine is downloaded from a CDN and cached in your browser on first use, then reusable offline.
What if the results aren’t accurate?
OCR accuracy depends on the clarity, size and contrast of the on-screen text. If results aren’t ideal, try: confirming the right language, using a smaller sampling interval, using “Bottom subtitle area only” for bottom subtitles, or first sharpening the video with our other tools. It’s a good idea to proofread the exported results.