PT Journal
AU Lluis Gomez
   Dimosthenis Karatzas
TI A fast hierarchical method for multi‐script and arbitrary oriented scene text extraction
SO International Journal on Document Analysis and Recognition
JI IJDAR
PY 2016
BP 335
EP 349
VL 19
IS 4
DE scene text; segmentation; detection; hierarchical grouping; perceptual organisation
AB Typography and layout lead to the hierarchical organisation of text in words, text lines, paragraphs. This inherent structure is a key property of text in any script and language, which has nonetheless been minimally leveraged by existing text detection methods. This paper addresses the problem of textsegmentation in natural scenes from a hierarchical perspective.Contrary to existing methods, we make explicit use of text structure, aiming directly to the detection of region groupings corresponding to text within a hierarchy produced by an agglomerative similarity clustering process over individual regions. We propose an optimal way to construct such an hierarchy introducing a feature space designed to produce text group hypotheses withhigh recall and a novel stopping rule combining a discriminative classifier and a probabilistic measure of group meaningfulness based in perceptual organization. Results obtained over four standard datasets, covering text in variable orientations and different languages, demonstrate that our algorithm, while being trained in a single mixed dataset, outperforms state of the artmethods in unconstrained scenarios.
ER