PT Unknown
AU Lluis Gomez
   Dimosthenis Karatzas
TI Multi-script Text Extraction from Natural Scenes
BT 12th International Conference on Document Analysis and Recognition
PY 2013
BP 467
EP 471
DI 10.1109/ICDAR.2013.100
AB Scene text extraction methodologies are usually based in classification of individual regions or patches, using a priori knowledge for a given script or language. Human perception of text, on the other hand, is based on perceptual organisation through which text emerges as a perceptually significant group of atomic objects. Therefore humans are able to detect text even in languages and scripts never seen before. In this paper, we argue that the text extraction problem could be posed as the detection of meaningful groups of regions. We present a method built around a perceptual organisation framework that exploits collaboration of proximity and similarity laws to create text-group hypotheses. Experiments demonstrate that our algorithm is competitive with state of the art approaches on a standard dataset covering text in variable orientations and two languages.
ER