Text-Based CAPTCHAs
Complexity: ⭐ (Low)
How it looks:
How to identify:
- Distorted, wavy, or scratched text
- Random letters and numbers
- Lines or noise overlay
- Sometimes colored background
Demo to try it yourself:
- Basic text CAPTCHA demo: captcha.com – Text CAPTCHA demo
Free & open-source bypass methods
| Tool | Description | Success Rate | Link | |——|————-|————–|——| | ddddocr | 🔥 Best for simple CAPTCHAs, works out of box | 90-99% | sml2h3/ddddocr | | EasyOCR | Multi-language OCR, good accuracy | 70-90% | JaidedAI/EasyOCR | | PaddleOCR | Powerful OCR, great for complex text | 80-95% | PaddlePaddle/PaddleOCR | | Tesseract | Classic OCR, needs preprocessing | 50-80% | tesseract-ocr/tesseract | | captcha_trainer | Train your own model | 95-99% | kerlomz/captcha_trainer | | MMOCR | OCR toolkit from OpenMMLab with many models | 80-98% | open-mmlab/mmocr | | TrOCR | Transformer-based OCR (Hugging Face) | 85-98% | microsoft/trocr-base | | CRNN baselines | Lightweight CNN+RNN text recognizers | 80-95% | meijieru/crnn.pytorch |
Preprocessing tricks to boost OCR
- Convert to grayscale → adaptive threshold (e.g., Otsu) to remove background noise.
- Deskew/rotate to horizontal text.
- Morphology (dilate/erode) to reconnect broken strokes; remove thin noise with opening.
- Median/gaussian blur to reduce speckles; bilateral filter to keep edges.
- Resize 2–4× with lanczos before OCR.
- Invert colors if foreground/background is inverted.
- Segment characters (vertical projection) and run per-character OCR when spacing is big.
Custom training options
- Collect 2–5k synthetic samples using fonts + noise similar to target CAPTCHA.
- Train with captcha_trainer, MMOCR, or a CRNN in PyTorch/TensorFlow.
- Use CTC loss for variable-length strings; augment with elastic distortions, blur, salt & pepper, random lines.
- Export to ONNX/TensorRT for fast inference.
Cloud / vision APIs (when allowed)
| Service | Notes | |———|——-| | Google Cloud Vision | Strong on warped text; pay-per-use | | AWS Textract | Good multi-language support | | Azure Read | Solid printed-text OCR | | GPT-4o / Gemini Vision | Vision-LMMs can solve many low-complexity text CAPTCHAs |
💰 Paid alternatives:
If free methods don’t work, use API services:
| Service | Price (per 1000) | Speed | Link |
|---|---|---|---|
| 2Captcha | $0.50 - $1.00 | 10-30s | 2captcha.com |
| Anti-Captcha | $0.50 - $1.00 | 10-30s | anti-captcha.com |
| CapSolver | $0.40 - $0.80 | 5-20s | capsolver.com |
| CapMonster | $0.40 - $0.90 | 10-25s | capmonster.cloud |
| DeathByCaptcha | $1.39 | 15-30s | [deathbycaptcha.com](https://deathbycaptcha.com/api#api_details_upload_captcha |
📊 Quick decision guide
- Try ddddocr first (fast, high accuracy on simple text).
- If noisy/warped: preprocess (binarize, deskew, denoise) then PaddleOCR/MMOCR.
- Need maximum accuracy or custom font: train with captcha_trainer or CRNN on synthetic data.
- Want hands-off: use paid solvers (2Captcha/Anti-Captcha/CapSolver).