Smart Real-Time Object Detection for Blind Individuals

The integration of real-time object detection with advanced text-to-speech (TTS) systems offers transformative potential for enhancing accessibility for visually impaired individuals.This paper presents a system employing cutting-edge artificial intelligence (AI) techniques, specifically YOLOv8 for object detection and Tesseract OCR for text recognition, to process visual data into audible feedback.The system achieves real-time performance with a robust architecture that integrates preprocessing, detection, and audio feedback modules.Testing demonstrates approximately 90% accuracy in object detection and 85% accuracy in text recognition, paving the way for a scalable and user-friendly assistive technology.Furthermore, the system's adaptability to diverse environments and seamless integration with existing technologies underline its utility in addressing accessibility challenges.

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Publication Details

Journal
Science Education and Innovations in the Context of Modern Problems
Published
2024-12-10
DOI
https://doi.org/10.56334/sei/7.4.11
Primary Topic
Video Surveillance and Tracking Methods
Type
article
Field-Weighted Citation Impact
0.00
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article

Smart Real-Time Object Detection for Blind Individuals

Rajeev Bilagi
Science Education and Innovations in the Context of Modern Problems
Video Surveillance and Tracking Methods
article

Smart Real-Time Object Detection for Blind Individuals

Rajeev Bilagi
article en

Abstract

The integration of real-time object detection with advanced text-to-speech (TTS) systems offers transformative potential for enhancing accessibility for visually impaired individuals.This paper presents a system employing cutting-edge artificial intelligence (AI) techniques, specifically YOLOv8 for object detection and Tesseract OCR for text recognition, to process visual data into audible feedback.The system achieves real-time performance with a robust architecture that integrates preprocessing, detection, and audio feedback modules.Testing demonstrates approximately 90% accuracy in object detection and 85% accuracy in text recognition, paving the way for a scalable and user-friendly assistive technology.Furthermore, the system's adaptability to diverse environments and seamless integration with existing technologies underline its utility in addressing accessibility challenges.

Science Education and Innovations in the Context of Modern ProblemsVol. 7(4)
Openalex Percentile: Top 71%
Video Surveillance and Tracking Methods
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