🔐 VerifyMe.AI

AI-powered CAPTCHA system using face and hand gesture recognition for secure human verification.

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📌 Project Summary

VerifyMe.AI replaces traditional CAPTCHA methods with a smart, real-time human verification system. It uses webcam-based face detection and hand gesture recognition to ensure that only real users — not bots — pass through security checks.

This system is ideal for online exams, secure login systems, or kiosk-based public services. The user is asked to perform a random challenge (e.g., show 2 fingers and smile), and the system verifies both face presence and gesture correctness.

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🎯 Key Features

• ✅ Detects and verifies human face using Haar Cascades
• ✋ Identifies hand gestures (1–5 fingers) using Mediapipe
• 🎥 Works in real-time using webcam
• 🔐 Enhanced security against bots and spoofing
• 💡 Can be extended to mobile, web, or kiosk systems

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🧠 Real-World Applications

Use Case	Examples
Online exam portals	Facial + gesture login for human candidates
Government portals	Secure public access (UIDAI, IRCTC, etc.)
Banking Kiosks	Face + hand check before e-KYC
Cybercafés	Prevent bots from auto-registering

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🛠️ Technologies Used

• Python 3.8
• OpenCV – for webcam and face detection
• Mediapipe – for hand landmark tracking
• Haarcascade XML – pre-trained face detection model
• NumPy – image/array operations

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📁 Folder Structure

verifyme-ai/
├── app.py                        # Main script to run system
├── requirements.txt              # Dependencies list
├── LICENSE                       # MIT License
├── README.md                     # This file
│
├── haarcascades/
│   └── haarcascade_frontalface_default.xml
│
├── hand_module/
│   └── hand_gesture.py           # Hand gesture detection logic
│
├── assets/
│   └── bala.jpg                  # Test image or user sample
│
└── .venv/                        # Virtual environment (optional)

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📥 Installation Guide

✅ Step 1: Clone the Repository

git clone https://github.com/yourusername/verifyme-ai.git
cd verifyme-ai

✅ Step 2: Create a Virtual Environment

python -m venv .venv

✅ Step 3: Activate the Environment

• Windows:

  .venv\Scripts\activate

• Linux/macOS:

  source .venv/bin/activate

✅ Step 4: Install Dependencies

pip install -r requirements.txt

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▶️ How to Run

python app.py

1. The webcam will start.
2. The system will detect your face using Haar Cascade.
3. A random gesture challenge appears (e.g., "Show 3 fingers").
4. Mediapipe detects your hand and counts fingers.
5. If both checks pass → ✅ CAPTCHA Passed

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🔍 How It Works (Flowchart)

[ Webcam Feed ]
       ↓
[ Detect Face (Haar Cascade) ]
       ↓
[ Detect Hand (Mediapipe) ]
       ↓
[ Generate Random Gesture Challenge ]
       ↓
[ Match Face + Gesture ]
       ↓
[ Verification Success ]

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🧪 Sample Challenge Logic (Python)

import random
challenge = random.choice([1, 2, 3, 4, 5])
print(f"Show {challenge} fingers to continue")

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💡 Example Code Snippet: Face Detection (OpenCV)

face_cascade = cv2.CascadeClassifier('haarcascades/haarcascade_frontalface_default.xml')
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)

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🖐️ Example Code: Hand Landmark Detection (Mediapipe)

with mp_hands.Hands() as hands:
    result = hands.process(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
    if result.multi_hand_landmarks:
        count_fingers(result.multi_hand_landmarks)

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📷 Demo Preview

![demo]

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🚀 Future Enhancements

• GUI using Tkinter or Streamlit
• Mobile version using MediaPipe on Android
• OTP fallback for invalid attempts
• Smile/blink detection (multi-modal verification)
• Voice command captcha support

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👨‍💻 Author

Balashanmugam
MSc Data Science | AI Enthusiast | Python Developer
📧 balashanmugamrathinam@gmail.com
🔗 LinkedIn Profile

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📝 License

This project is licensed under the LICENSE.
You are free to use, modify, and distribute this code for personal or commercial use.

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“VerifyMe.AI: Making CAPTCHA smarter, not harder.”