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ICPR
2002
IEEE

A Robust Approach for Recognition of Text Embedded in Natural Scenes

13 years 7 months ago
A Robust Approach for Recognition of Text Embedded in Natural Scenes
In this paper, we propose a robust approach for recognition of text embedded in natural scenes. Instead of using binary information as most other OCR systems do, we extract features from intensity of an image directly. We utilize a local intensity normalization method to effectively handle lighting variations. We then employ Gabor transform to obtain local features, and use LDA for selection and classification of features. The proposed method has been applied to a Chinese sign recognition task. The system can recognize a vocabulary of 3755 Level 1 Chinese characters in the Chinese national standard character set GB2312-80 with various print fonts. We tested the system on 1630 test characters in sign images captured from the natural scenes, and the recognition accuracy is 92.46%. We have already integrated the system into our automatic Chinese sign translation system.
Jing Zhang, Xilin Chen, Andreas Hanneman, Jie Yang
Added 14 Jul 2010
Updated 14 Jul 2010
Type Conference
Year 2002
Where ICPR
Authors Jing Zhang, Xilin Chen, Andreas Hanneman, Jie Yang, Alex Waibel
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