| Authors |
Georg Poier, Jürgen Hatzl, Stefan Kluckner, Roth Peter M., Bischof Horst |
| Appeared in |
In Proc. Computer Vision Winterworkshop |
| Date |
2012 |
| Abstract |
Text localization is the first step when automatically reading text in images.
Since existing methods often fail when applied to unconstrained images, in this
paper we propose a more robust approach exploiting different kind of
information. In particular, we first extract textural features, a combination of
a stroke filter with a super-pixel segmentation, and then search for connected
components. To finally obtain a text localization, these are subsequently
analyzed for unary character properties, binary character similarities, and text
line properties. To demonstrate the benefits of the proposed method, we evaluate
it on three different data sets, showing promising results. |
| Link |
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