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Text Localization in Natural Scene Images Based on Conditional Random Field

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3 Author(s)
Yi-Feng Pan ; Nat. Lab. of Pattern Recognition, Chinese Acad. of Sci., Beijing, China ; Xinwen Hou ; Cheng-Lin Liu

This paper proposes a novel hybrid method to robustly and accurately localize texts in natural scene images. A text region detector is designed to generate a text confidence map, based on which text components can be segmented by local binarization approach. A conditional random field (CRF) model, considering the unary component property as well as binary neighboring component relationship, is then presented to label components as "text" or "non-text". Last, text components are grouped into text lines with an energy minimization approach. Experimental results show that the proposed method gives promising performance comparing with the existing methods on ICDAR 2003 competition dataset.

Published in:

Document Analysis and Recognition, 2009. ICDAR '09. 10th International Conference on

Date of Conference:

26-29 July 2009

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