| 论文标题 |
Multilingual corpus construction based on printed and handwritten character separation |
| 作者 |
Yuping Lin, Yonghong Song, Yingyu Li, et al |
| 发表/完成日期 |
2015-10-24 |
| 期刊名称 |
Multimedia Tools & Applications |
| 期卷 |
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| 相关文章 |
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| 论文简介 |
This paper proposes an effective method to extract printed and handwritten characters
from multilingual document images to build corpus. To extract the characters from the
document images, a connected component analysis method is used to remove the graphics.
After that, multiple types of features and AdaBoost algorithm are introduced to classify printed
and handwritten characters in a more versatile and robust way. Firstly, the content of the image
is divided into several text patches which are then used to distinguish different languages.
Secondly, we use the multiple types of features and AdaBoost algorithm to train the classifiers
based on the segmented patches. Finally, we can separate printed and handwritten parts of new
image set by the trained classifiers. The proposed method improves the precision of the
extraction of written materials in text images of different languages. Experimental results
demonstrate that the proposed method is more accurate in terms of precision and recall rate
compared with the state-of the-art methods.
DOI 10.1007/s11042-015-2995-5 |
(创新港)
