Journal of Computer Science

TEXT SIGNAGE RECOGNITION IN ANDROID MOBILE DEVICES

Oi-Mean Foong, Suziah Sulaiman and Kiing Kiu Ling

DOI : 10.3844/jcssp.2013.1793.1802

Journal of Computer Science

Volume 9, Issue 12

Pages 1793-1802

Abstract

This study presents a Text Signage Recognition (TSR) model in Android mobile devices for Visually Impaired People (VIP). Independence navigation is always a challenge to VIP for indoor navigation in unfamiliar surroundings. Assistive Technology such as Android smart devices has great potential to assist VIPs in indoor navigation using built-in speech synthesizer. In contrast to previous TSR research which was deployed in standalone personal computer system using Otsu’s algorithm, we have developed an affordable Text Signage Recognition in Android Mobile Devices using Tesseract OCR engine. The proposed TSR model used the input images from the International Conference on Document Analysis and Recognition (ICDAR) 2003 dataset for system training and testing. The TSR model was tested by four volunteers who were blind-folded. The system performance of the TSR model was assessed using different metrics (i.e., Precision, Recall, F-Score and Recognition Formulas) to determine its accuracy. Experimental results show that the proposed TSR model has achieved recognition rate satisfactorily.

Copyright

© 2013 Oi-Mean Foong, Suziah Sulaiman and Kiing Kiu Ling. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.