Title :
On Combining Multiple Segmentations in Scene Text Recognition
Author :
Neumann, Luka ; Matas, Jose
Author_Institution :
Dept. of Cybern., Czech Tech. Univ., Prague, Czech Republic
Abstract :
An end-to-end real-time scene text localization and recognition method is presented. The three main novel features are: (i) keeping multiple segmentations of each character until the very last stage of the processing when the context of each character in a text line is known, (ii) an efficient algorithm for selection of character segmentations minimizing a global criterion, and (iii) showing that, despite using theoretically scale-invariant methods, operating on a coarse Gaussian scale space pyramid yields improved results as many typographical artifacts are eliminated. The method runs in real time and achieves state-of-the-art text localization results on the ICDAR 2011 Robust Reading dataset. Results are also reported for end-to-end text recognition on the ICDAR 2011 dataset.
Keywords :
Gaussian processes; image segmentation; text detection; ICDAR 2011 robust reading dataset; character segmentations; coarse Gaussian scale space pyramid; end-to-end real-time scene text localization method; end-to-end text recognition; global criterion; multiple segmentations; scale-invariant methods; scene text recognition method; text line; typographical artifacts; Character recognition; Context; Detectors; Image segmentation; Robustness; Standards; Text recognition; photo OCR; scene text localization; scene text recognition; text-in-the-wild; unconstrained end-to-end text recognition;
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2013 12th International Conference on
Conference_Location :
Washington, DC
DOI :
10.1109/ICDAR.2013.110