DocumentCode :
2142459
Title :
A Method for Removing Inflectional Suffixes in Word Spotting of Mongolian Kanjur
Author :
Wei, Hongxi ; Gao, Guanglai ; Bao, Yulai
Author_Institution :
Sch. of Comput. Sci., Inner Mongolia Univ., Hohhot, China
fYear :
2011
fDate :
18-21 Sept. 2011
Firstpage :
88
Lastpage :
92
Abstract :
According to characteristics of Mongolian word-formation, a method for removing inflectional suffixes from word images of the Mongolian Kanjur is proposed in this paper. By removing inflectional suffixes, the amount of clusters equivalent indexing terms might be reduced in word spotting. For the above purpose, we need to determine whether or not one word image contains inflectional suffix. If the word image contains inflectional suffix, the inflectional suffix would be segmented from the word image. The proposed method is as follows: first, many parts are segmented from the bottom of the word image according to the cutting positions of the inflectional suffixes. Then, the segmented parts are represented by a number of profile features and classified by multi-BP neural networks. Finally, the outputs of BP are confirmed by template matching using DTW. Experimental results on our data set prove the feasibility of the proposed method.
Keywords :
backpropagation; document image processing; history; image classification; image matching; image segmentation; Mongolian Kanjur; Mongolian word formation; dynamic time warping; historical document; image classification; indexing terms; inflectional suffix removal; inflectional suffix segmentation; multiBP neural network; profile feature; template matching; word images; word spotting; Accuracy; Feature extraction; Image segmentation; Indexing; Neurons; Text analysis; Vectors; BP neural network; Mongolian Kanjur; inflectional suffix; template matching; word soptting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Document Analysis and Recognition (ICDAR), 2011 International Conference on
Conference_Location :
Beijing
ISSN :
1520-5363
Print_ISBN :
978-1-4577-1350-7
Electronic_ISBN :
1520-5363
Type :
conf
DOI :
10.1109/ICDAR.2011.27
Filename :
6065282
Link To Document :
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