DocumentCode :
2217725
Title :
An efficient binarization method for ancient Mongolian document images
Author :
Wei, Hongxi ; Gao, Guanglai ; Bao, Yulai ; Wang, Yali
Author_Institution :
Sch. of Comput. Sci., Inner Mongolia Univ., Hohhot, China
Volume :
2
fYear :
2010
fDate :
20-22 Aug. 2010
Abstract :
In order to recognize and retrieve the Mongolian Kanjur images, lots of preprocessing tasks should be done. In this paper, we concentrate on the binarization of the Mongolian Kanjur images and we have proposed an efficient binarization method for them. The proposed method is applied to each image as follows: First, some preprocessing tasks including grayscaling and smoothing are executed. Second, three well-known global thresholding methods are used for extracting regions of interest (ROIs) from every gray-level image. Then, each ROI is processed by a modified Sauvola´s algorithm with variant sizes of the small windows. Experimental results have proved that the proposed binarization method is better than the original Sauvola´s algorithm.
Keywords :
document image processing; grey systems; smoothing methods; Mongolian Kanjur image; Sauvola algorithm; ancient Mongolian document image; binarization method; gray-level image; grayscaling; region of interest; smoothing; Artificial neural networks; Mongolian Kanjur; binarization; document image; region of interest (ROI);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location :
Chengdu
ISSN :
2154-7491
Print_ISBN :
978-1-4244-6539-2
Type :
conf
DOI :
10.1109/ICACTE.2010.5579111
Filename :
5579111
Link To Document :
بازگشت