Text Localization in Real-World Images Using Efficiently Pruned Exhaustive Search
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F11%3A00187378" target="_blank" >RIV/68407700:21230/11:00187378 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1109/ICDAR.2011.144" target="_blank" >http://dx.doi.org/10.1109/ICDAR.2011.144</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICDAR.2011.144" target="_blank" >10.1109/ICDAR.2011.144</a>
Alternative languages
Result language
angličtina
Original language name
Text Localization in Real-World Images Using Efficiently Pruned Exhaustive Search
Original language description
An efficient method for text localization and recognition in real-world images is proposed. Thanks to effective pruning, it is able to exhaustively search the space of all character sequences in real time (200ms on a 640x480 image). The method exploits higher-order properties of text such as word text lines. We demonstrate that the grouping stage plays a key role in the text localization performance and that a robust and precise grouping stage is able to compensate errors of the character detector. Themethod includes a novel selector of Maximally Stable Extremal Regions (MSER) which exploits region topology. Experimental validation shows that 95.7% characters in the ICDAR dataset are detected using the novel selector of MSERs with a low sensitivity threshold. The proposed method was evaluated on the standard ICDAR 2003 dataset where it achieved state-of-the-art results in both text localization and recognition.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
<a href="/en/project/7E10045" target="_blank" >7E10045: Massive Sets of Heuristics for Machine Learning</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Document Analysis and Recognition (ICDAR), 2011 International Conference on
ISBN
978-1-4577-1350-7
ISSN
1520-5363
e-ISSN
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Number of pages
5
Pages from-to
687-691
Publisher name
IEEE Computer Society
Place of publication
Los Alamitos
Event location
Beijing
Event date
Sep 18, 2011
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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