DocumentCode :
1599873
Title :
Multi-scale texture-based text recognition in ancient manuscripts
Author :
Garz, Angelika ; Sablatnig, Robert
Author_Institution :
Comput. Vision Lab., Vienna Univ. of Technol., Vienna, Austria
fYear :
2010
Firstpage :
336
Lastpage :
339
Abstract :
Text recognition in ancient documents poses specific challenges such as degradation and staining, fading out of ink, fluctuating text lines, superimposing of text-elements or varying layouts, amongst others. To cope with those challenges, a texture-based approach is proposed, which exploits the fact that different kinds of textures have distinct orientation distributions. The orientation information is extracted using the Auto-Correlation Function (ACF). The approach is applied to three different manuscripts, namely to Glagolitic manuscripts of the 11th century, a Latin and a composite Latin-German manuscript, both originating from the 14th century. The evaluation is based on manually labeled ground truth and shows the accuracy of the features chosen even when the method is applied to document pages that are different in writing style and line spacing to those in the training set.
Keywords :
history; image classification; natural language processing; text analysis; Glagolitic manuscript; Latin-German manuscript; ancient manuscript; autocorrelation function; document page; multiscale texture based text recognition; orientation distribution; text line; varying layout; Feature extraction; Ink; Layout; Pixel; Shape; Text recognition; Writing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Virtual Systems and Multimedia (VSMM), 2010 16th International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-9027-1
Electronic_ISBN :
978-1-4244-9026-4
Type :
conf
DOI :
10.1109/VSMM.2010.5665938
Filename :
5665938
Link To Document :
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