Please use this identifier to cite or link to this item:
|Title:||Character extraction in web image for text recognition|
|Citation:||Su, B.,Lu, S.,Phan, T.Q.,Tan, C.L. (2012). Character extraction in web image for text recognition. Proceedings - International Conference on Pattern Recognition : 3042-3045. ScholarBank@NUS Repository.|
|Abstract:||Images with text are frequently used on Internet for different purposes. Automatic recognition of text from web images plays an important role on extraction and retrieval of web information. However, the web images are usually in low resolution with artifacts and special effects, which makes word recognition a challenge task even after the text has been localized. In this paper, we propose a robust text recognition technique to efficiently convert the web images into text format. The proposed technique first makes use of the L0 norm smoothing to increase the edge contrast of the input web images. The images are then binarized on each color channel. A connected component analysis is followed to identify the possible character components. Finally the character candidates are recognized by the OCR engine after skew correction. Extensive experiments have been conducted on the latest ICDAR 2011 robust reading competition dataset for born-digital text. The experimental results show the superior performance of our proposed technique. © 2012 ICPR Org Committee.|
|Source Title:||Proceedings - International Conference on Pattern Recognition|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Oct 27, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.