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DAS
2008
Springer

A Robust System to Detect and Localize Texts in Natural Scene Images

10 years 1 months ago
A Robust System to Detect and Localize Texts in Natural Scene Images
In this paper, we present a robust system to accurately detect and localize texts in natural scene images. For text detection, a region-based method utilizing multiple features and cascade AdaBoost classifier is adopted. For text localization, a window grouping method integrating text line competition analysis is used to generate text lines. Then within each text line, local binarization is used to extract candidate connected components (CCs) and non-text CCs are filtered out by Markov Random Fields (MRF) model, through which text line can be localized accurately. Experiments on the public benchmark ICDAR 2003 Robust Reading and Text Locating Dataset 1 show that our system is comparable to the best existing methods both in accuracy and speed.
Yi-Feng Pan, Xinwen Hou, Cheng-Lin Liu
Added 19 Oct 2010
Updated 19 Oct 2010
Type Conference
Year 2008
Where DAS
Authors Yi-Feng Pan, Xinwen Hou, Cheng-Lin Liu
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