Portable Camera-Based Product Label Reading For Blind People
Rajkumar N, Anand M.G, Barathiraja N

TL;DR
This paper presents a portable camera-based system that helps blind people read product labels by isolating objects through motion, localizing text with a learning algorithm, and converting it into audio, demonstrating high accuracy and user effectiveness.
Contribution
It introduces a novel motion-based ROI detection and a gradient feature learning algorithm for text localization, improving assistive reading for the visually impaired.
Findings
Achieves high accuracy on ICDAR datasets
Effective in complex background scenarios
Validated with real blind users
Abstract
We propose a camera-based assistive text reading framework to help blind persons read text labels and product packaging from hand-held objects in their daily life. To isolate the object from untidy backgrounds or other surrounding objects in the camera vision, we initially propose an efficient and effective motion based method to define a region of interest (ROI) in the video by asking the user to tremble the object. This scheme extracts moving object region by a mixture-of-Gaussians-based background subtraction technique. In the extracted ROI, text localization and recognition are conducted to acquire text details. To automatically focus the text regions from the object ROI, we offer a novel text localization algorithm by learning gradient features of stroke orientations and distributions of edge pixels in an Adaboost model. Text characters in the localized text regions are then…
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