An Efficient OCR System For Visually Impaired

Abstract: The major problem faced by visually impaired people is that they are unable to do text recognition on their own, which forces them to depend on others for their day to day activities such as reading newspapers, letters sent through post, referring books etc. The aim of this project is to develop an Optical Character Recognition (OCR) system integrated into an academic system which is designed to improve accessibility for visually impaired students, teachers, and administrators. This system uses advanced OCR technology, combined with image processing, Text-to-Speech Conversion (TTS) and machine learning algorithms, to convert printed text into a digital format. The key objective is to ensure that visually impaired users can access educational, administrative, and communicative resources seamlessly and can be recognized text into spoken words. For students, the OCR system allows them to access a variety of academic resources, such as textbooks, class notes, assignments, schedules, and exam papers, in an accessible digital format. The system can instantly extract text from documents and convert it into a format that is compatible with Text-to-Speech software, enabling students to interact with materials independently. Furthermore, students can benefit from multi-language support, ensuring they can access information in their preferred language. For teachers, the OCR system provides the ability to convert printed or handwritten teaching materials and notices into accessible formats for their visually impaired students. Teachers can scan documents and instantly create digital copies that are compatible with assistive technologies. This facilitates smoother distribution of teaching resources and more inclusive classroom engagement. Teachers can also use the system to modify documents to meet specific needs of students, enhancing personalized learning.

Keywords: OCR, TTS, Visual Impairment, Accessibility, Assistive Technology