Abstract: Smart Reader is designed as an accessibility-focused system that supports non-visual reading by combining text recognition, scene understanding, audio guidance, and tactile cues. The platform utilizes a pair of complementary OCR engines in concert with a lightweight object-analysis module to interpret both text and surrounding context from incoming video frames. Such an optimized backend, implemented on top of Fast API, empowers the pipeline to handle each frame within about two hundred milliseconds, which can enable several frames per second on regular CPU hardware. A specially designed mapping function transforms the OCR characteristics, including confidence levels, text density, and semantic weight, into structured vibration signals that help users haptically perceive document layout. Experimental studies have shown higher recognition reliability than using a single OCR method alone, along with consistent detection quality and responsive system behavior. In general, Smart Reader provides an improved pathway for visually impaired users to access printed or on-screen information based on a powerful combination of perception, interpretation, and haptic assistance.
Keywords: OCR, Haptic Feedback, YOLOv8, Assistive Technology, Fast API, Real-Time Processing.
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DOI:
10.17148/IJARCCE.2025.141298
[1] Dr. T. R. Muhibur Rahman, Prashanth J, Karnatakam Sai Anirudh, Jagat Singh, Haseeb Ahmed S, "A Real-Time Multimodal Assistive Framework Integrating Ensemble OCR, Object Detection, Text Analytics, and Haptic Feedback," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.141298
