%0 Conference Proceedings
%T Text Detection in Urban Scenes (video sample)
%A Sergio Escalera
%A Xavier Baro
%A Jordi Vitria
%A Petia Radeva
%B 12th International Conference of the Catalan Association for Artificial Intelligence
%D 2009
%V 202
%@ 978-1-60750-061-2
%F Sergio Escalera2009
%O OR;MILAB;HuPBA;MV
%O exported from refbase (http://refbase.cvc.uab.es/show.php?record=1181), last updated on Tue, 17 Dec 2013 13:19:35 +0100
%X 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
%U http://dx.doi.org/10.3233/978-1-60750-061-2-35
%P 35–44