BCN Perceptual Computing Lab Repository

Text Detection in Urban Scenes

Escalera, Sergio and Baró, Xavier and Vitrià, Jordi and Radeva, Petia (2009) Text Detection in Urban Scenes. In: Artificial Intelligence Resarch and Development, Frontiers in Artificial Intelligence and Applications. IOS Press, pp. 35-44. ISBN 978-1-60750-061-2

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Abstract

Text detection in urban scenes is a hard task due to the high variability of text appearance: different text fonts, changes in the point of view, or partial occlusion are just a few problems. Text detection can be specially suited for georeferencing business, navigation, tourist assistance, or to help visual impaired people. In this paper, we propose a general methodology to deal with the problem of text detection in outdoor scenes. The method is based on learning spatial information of gradient based features and Census Transform images using a cascade of classifiers. The method is applied in the context of Mobile Mapping systems, where a mobile vehicle captures urban image sequences. Moreover, a cover data set is presented and tested with the new methodology. The results show high accuracy when detecting multi-linear text regions with high variability of appearance, at same time that it preserves a low false alarm rate compared to classical approaches.

Item Type:Book Section
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
ID Code:38
Deposited By:INVALID USER
Deposited On:03 Nov 2009 19:30
Last Modified:29 Nov 2010 17:52

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