Camera-Based signage detection and recognition for blind persons

Authors:
Shuihua Wang;Yingli Tian
Affiliations:
Department of Electrical Engineering, The City College, City University of New York, New York, NY;Department of Electrical Engineering, The City College, City University of New York, New York, NY
Venue:
ICCHP'12 Proceedings of the 13th international conference on Computers Helping People with Special Needs - Volume Part II
Year:
2012

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Abstract

Signage plays an important role for wayfinding and navigation to assist blind people accessing unfamiliar environments. In this paper, we present a novel camera-based approach to automatically detect and recognize restroom signage from surrounding environments. Our method first extracts the attended areas which may content signage based on shape detection. Then, Scale-Invariant Feature Transform (SIFT) is applied to extract local features in the detected attended areas. Finally, signage is detected and recognized as the regions with the SIFT matching scores larger than a threshold. The proposed method can handle multiple signage detection. Experimental results on our collected restroom signage dataset demonstrate the effectiveness and efficiency of our proposed method.