TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

A method for text localization and recognition in real-world images

Tutkimustuotosvertaisarvioitu

Yksityiskohdat

AlkuperäiskieliEnglanti
OtsikkoComputer Vision, ACCV 2010 - 10th Asian Conference on Computer Vision, Revised Selected Papers
Sivut770-783
Sivumäärä14
Vuosikerta6494 LNCS
PainosPART 3
DOI - pysyväislinkit
TilaJulkaistu - 2011
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
Tapahtuma10th Asian Conference on Computer Vision, ACCV 2010 - Queenstown, Uusi-Seelanti
Kesto: 8 marraskuuta 201012 marraskuuta 2010

Julkaisusarja

NimiLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumeroPART 3
Vuosikerta6494 LNCS
ISSN (painettu)03029743
ISSN (elektroninen)16113349

Conference

Conference10th Asian Conference on Computer Vision, ACCV 2010
MaaUusi-Seelanti
KaupunkiQueenstown
Ajanjakso8/11/1012/11/10

Tiivistelmä

A general method for text localization and recognition in real-world images is presented. The proposed method is novel, as it (i) departs from a strict feed-forward pipeline and replaces it by a hypotheses-verification framework simultaneously processing multiple text line hypotheses, (ii) uses synthetic fonts to train the algorithm eliminating the need for time-consuming acquisition and labeling of real-world training data and (iii) exploits Maximally Stable Extremal Regions (MSERs) which provides robustness to geometric and illumination conditions. The performance of the method is evaluated on two standard datasets. On the Char74k dataset, a recognition rate of 72% is achieved, 18% higher than the state-of-the-art. The paper is first to report both text detection and recognition results on the standard and rather challenging ICDAR 2003 dataset. The text localization works for number of alphabets and the method is easily adapted to recognition of other scripts, e.g. cyrillics.