This project demonstrates a practical application of OCR (Optical Character Recognition) and CAPTCHA technologies to create a secure and efficient online form submission system. It's designed to be a starting point, and with further development and customization, it can be adapted to meet the specific needs of different examination systems.
- Python: Ensure you have Python installed on your machine.
Install the required Python libraries:
pip install flask pytesseract captcha Pillow
Execute the following command to start the Flask server:
python app.pyBy default, the application will run on http://127.0.0.1:5000/. Open this URL in your web browser to interact with the form.
- Flask: A lightweight WSGI web application framework in Python used to build the web server.
- Pytesseract: An OCR tool for Python to recognize text from images.
- CAPTCHA: A Python library to generate CAPTCHA images to prevent automated bots from submitting the form.
- HTML/CSS/JavaScript: Used for creating the frontend of the application, styling, and handling user interactions.
- Enhanced Security: Implement more robust CAPTCHA systems like reCAPTCHA to improve security against bots. 🔐
- User Authentication: Add user authentication to track and manage submissions more securely. 🔑
- Database Integration: Integrate a database to store and manage form submissions for retrieval and analysis. 💾
- Advanced OCR Features: Implement more sophisticated OCR features to handle various document types and layouts. 📚
- Responsive Design: Enhance the frontend with a responsive design to ensure the form is easily accessible on various devices. 📱
The OCR and CAPTCHA-enabled examination form is a testament to the power of combining various technologies to create secure and efficient digital solutions. As technology advances, the potential for further enhancements grows, making it an exciting area for continuous development and innovation.