Real-Time Object Recognition with Voice Feedback for Visually Impaired Based on Raspberry Pi

Visually impaired individuals rely on real-time object recognition to overcome the challenges posed by their limited visual capabilities. Traditional navigation for the visually impaired often involves the use of canes or guide dogs, but these methods have limitations, particularly when it comes to identifying specific objects, obstacles, or changes in the environment. Real-time object recognition technology utilizes cameras and advanced algorithms to identify and interpret visual information in real-time, providing auditory or haptic feedback to users. This capability enables visually impaired individuals to access instant information about their surroundings, such as recognizing familiar objects, reading signs, avoiding obstacles, and navigating through complex environments independently. This technology enhances their spatial awareness and allows them to make informed decisions, promoting greater autonomy and reducing reliance on external assistance. Hence, in this work an efficient approach to address the challenges faced by visually impaired individuals through the development of a real-time object recognition system with voice feedback has been designed. The proposed system leverages the capabilities of Raspberry Pi, integrating computer vision techniques to identify objects in the surroundings. In real-time, the system processes live video input from a camera, identifies objects, and provides instant auditory feedback to the user through a voice interface. The proposed system accuracy and efficiency are evaluated through comprehensive testing, demonstrating its potential as an assistive technology to enhance the liberation and security of visually impaired users in home environments.