🔍 KYC Verification Platform

Overview

The KYC (Know Your Customer) Verification Platform is designed to ensure user authenticity through advanced image verification techniques. This platform captures a live image of the user, verifies it against a provided ID document, and checks an additional image uploaded by the user against a database for potential matches.

📑 Table of Contents

• ✨ Features
• 🔄 Workflow
• 🛠 Key Components
• 🏆 Judging Criteria
• 🎯 Bonus Challenges
• ⚙️ Installation
• 🚀 Usage
• 🔧 Configuration
• 📦 Dependencies
• ❓ Troubleshooting
• 👥 Contributors
• 📝 License

✨ Features

• User-Friendly Interface: Intuitive landing page guiding users through the verification process.
• 📸 Live Image Capture: Utilizes the device camera to capture a live image of the user.
• 🛡 CAPTCHA Verification: Verifies user presence through a CAPTCHA that requires verbal confirmation.
• 📄 Document Upload: Allows users to upload an official ID document for facial verification.
• 🔍 Image Comparison: Compares the live image with the ID document and checks an additional random image against a database.
• 📊 Embedding and Similarity Scoring: Provides the top K similar images from the database with respective similarity scores.

🔄 Workflow

1. 🌐 Landing Page:
   Users begin on a welcoming landing page, which explains the platform and introduces the verification process. They are prompted to click "Get Started" to initiate the verification.

2. 📷 Camera Activation:
   Once users click "Get Started," their device’s camera is activated. This interface allows users to capture a live image of themselves. The platform ensures that the camera setup is intuitive, making it easy for users to proceed with the capture.

3. 🛡 CAPTCHA Verification:
   To verify the user’s presence and ensure the live image is being captured in real-time, the platform presents a CAPTCHA on the screen. Users are asked to verbally say the characters shown, adding an extra layer of security and confirming their presence.

4. 🖼 Document Image Upload:
   After successfully completing the CAPTCHA, users are prompted to upload an official ID document (e.g., passport, driver’s license). This document will later be used for comparison with the live image captured earlier.

5. 🔍 Image Comparison:
   The platform then processes both the live image and the uploaded document, comparing the two to verify if the faces match. This step ensures the user’s identity is legitimate and consistent across both images.

6. 📂 Random Image Upload and Database Comparison:
   Users are asked to upload one more image, typically a random photo. This image is checked against a larger database for potential matches, and the system provides similarity scores for the top K similar images.

7. 📊 Embedding and Similarity Check:
   During this step, the platform generates embeddings (numerical representations of the images) and compares them with images in the database. This ensures the user's images are accurately matched with any potential duplicates or similar faces in the system.

8. ✅ Completion:
   Once all the verification steps are complete, users receive feedback on their verification status. The system informs them whether their identity has been successfully verified or if further steps are needed. The entire process is designed to be smooth and informative, keeping the user updated at each stage.

🛠 Key Components

• 👁️ Liveness Detection: Ensures the live image is genuine through methods like blinking detection and head movement.
• 📁 Flexible Image Formats: Supports various formats and conditions for accurate facial recognition.
• ⚡ Efficient Database Search: Employs algorithms for fast and reliable image comparisons.
• 📈 Scalability: Designed to handle high user volumes without compromising performance.

🏆 Judging Criteria

• 👁️‍🗨️ Liveness Verification: Effectiveness in determining if the user's image is live.
• 🤖 Facial Recognition Accuracy: Ability to handle diverse scenarios and maintain high accuracy.
• 🚀 Performance and Speed: Overall efficiency of the platform's operations.
• 🔎 Image Comparison Logic: Speed and accuracy of image comparisons against the database.

🎯 Bonus Challenges

• 🤖 AI-Generated Image Detection: Feature to identify if uploaded images are artificially generated.
• 🎨 User Engagement Features: Enhancements to improve overall user experience.

⚙️ Installation

1. Clone the repository:

  git clone https://github.com/prasukjain07/UpperCircuit.git

2.Drive Link for the implementation

https://drive.google.com/drive/u/3/folders/1QG6jH0X_9YUdGkwahCwjluvTf5QXUD6K

3. PPT

https://www.canva.com/design/DAGSFs0WMWU/aremOTevgcW-nNyALIozgA/edit?utm_content=DAGSFs0WMWU&utm_campaign=designshare&utm_medium=link2&utm_source=sharebutton