This project presents a smart glasses system designed to assist visually impaired individuals by providing real-time face recognition and auditory feedback. The system is built using a Raspberry Pi 3, equipped with a Pi Camera for image acquisition and a speaker for voice-based alerts. OpenCV and NumPy are employed for facial detection and recognition, enabling the identification of known individuals in the user’s environment. A Flask-based web application allows remote management, including training new faces and monitoring system performance. The system processes captured images, matches detected faces against a stored database, and provides real-time voice alerts to help users recognize people around them. This cost-effective and portable solution enhances social interactions and independence for visually impaired individuals by leveraging AI-driven face recognition technology.    

The objectives of the project are:

  Real-Time Face Recognition – Implement OpenCV and NumPy to detect and recognize faces, assisting visually impaired users in identifying people around them.

  Voice-Based Feedback System – Convert recognition results into auditory cues using a speaker, providing real-time information about detected individuals.

  Seamless Image Processing – Utilize OpenCV for image acquisition, preprocessing, and face matching to ensure efficient and accurate recognition.

  Flask-Based Web Interface – Develop a web-based application for remote management, allowing users or caregivers to add new faces to the database and monitor system performance.

  Portable and Cost-Effective Design – Build an affordable and lightweight solution using Raspberry Pi 3, ensuring accessibility for visually impaired individuals.

  Enhanced Social Interaction – Enable users to recognize familiar faces, improving confidence and independence in social environments.

  Secure and Efficient Database Management – Store and manage facial data securely while ensuring quick retrieval and comparison for real-time processing.

  Scalability and Customization – Provide an adaptable system that can integrate additional features like object detection, obstacle avoidance, or GPS navigation for future enhancements.      

The major building blocks of the project are:  

• Power supply.
• Raspberry Pi3 B+ processor.
• Pi Camera.
• SD card.

     

Software’s used:  

1. Python programming.
2. Raspbian OS.
3. Express SCH for Circuit design.
4. Face recognition using image processing.
5. HTML WEBPAGE.

   

video: