VisioLingua: IVIS (Intelligent Vision Interpretation System)
N J Avinash, Anushree, Zainab Zahid Hussain, Gaurav K, A B Jagathraj · 2025
Visually impaired individuals face significant challenges in accessing textual and Braille-based information, limiting their independence and engagement with the world. To address these issues, this work introduces an innovative assistive system that combines machine learning, computer vision, and text-to-speech technologies. This paper discusses the design and implementation of a system that enables real-time recognition and processing of printed text and Braille characters, converting them into audible speech for immediate use. Convolutional neural networks (CNNs) powered by TensorFlow and Keras ensure high accuracy in Braille character recognition. At the same time, OpenCV handles crucial image preprocessing steps such as grayscale conversion, thresholding, and contour detection. Text recognition is facilitated through Tesseract OCR, and the pyttsx3 library provides efficient multilingual text-to-speech conversion. Compact and user-friendly, the system has the potential to significantly improve the quality of life for visually impaired individuals by fostering independence and inclusivity.