ID Card Information Extraction AI System
A computer vision API application designed to extract detailed information from South African ID cards using AI and mobile photos.
Wed Jan 15 2025
AI
Computer Vision
Information Extraction
API
South Africa

This project is an advanced computer vision AI system designed to extract all available information from South African ID cards. By processing photos captured via mobile devices, the system uses AI models to detect and extract details such as names, ID numbers, dates of birth, and more. The results are transmitted back through an API, providing an efficient and automated solution for identity verification and data processing.
Features
- Comprehensive Data Extraction: Extracts all available information, including names, ID numbers, dates of birth, and issue dates.
- Mobile Compatibility: Processes high-quality images taken using mobile devices.
- AI-Driven Accuracy: Uses state-of-the-art computer vision models for reliable data extraction.
- Fast API Integration: Sends processed data through an API for seamless integration into existing systems.
- Secure Processing: Ensures data privacy and security during transmission and processing.
How It Works
- Image Capture: Users take photos of ID cards using their mobile devices.
- Image Processing: The system processes the images using computer vision models to detect and extract information.
- Data Extraction: Extracted details, such as names and ID numbers, are parsed and structured.
- API Transmission: The processed information is sent back via an API to the requesting application.
- Integration: Businesses or organizations integrate the data into their workflows for verification or record-keeping.
Challenges Faced
- Handling variations in lighting, angles, and image quality from mobile photos.
- Ensuring high accuracy for diverse formats of South African IDs (ID books and smart ID cards).
- Maintaining data security and compliance with privacy regulations.
Future Enhancements
- Expanding to support ID formats from other countries.
- Incorporating optical character recognition (OCR) enhancements for improved accuracy.
- Developing a user-friendly SDK for easier integration into mobile applications.
- Adding multi-language support for broader adoption.
- Implementing advanced fraud detection mechanisms to flag tampered or fake IDs.