Title :
Robust directional features for wordspotting in degraded Syriac manuscripts
Author :
Bilane, P. ; Bres, S. ; Emptoz, H.
Author_Institution :
LIRIS, INSA-Lyon, Lyon
Abstract :
This paper presents a contribution to Word Spotting applied for digitized Syriac manuscripts. The Syriac language was wrongfully accused of being a dead language and has been set aside by the domain of handwriting recognition. Yet it is a very fascinating handwriting that combines the word structure and calligraphy of the Arabic handwriting with the particularity of being intentionally written tilted by an angle of approximately 45deg. For the spotting process, we developed a method that should find all occurrences of a certain query word image, based on a selective sliding window technique, from which we extract directional features and afterwards perform a matching using Euclidean distance correspondence between features. The proposed method does not require any prior information, and does not depend of a word to character segmentation algorithm which would be extremely complex to realize due to the tilted nature of the handwriting.
Keywords :
document image processing; feature extraction; handwriting recognition; handwritten character recognition; Arabic handwriting calligraphy; Euclidean distance; character segmentation algorithm; degraded Syriac manuscripts; handwriting recognition; query word image; sliding window technique; word spotting; Data mining; Degradation; Euclidean distance; Feature extraction; Handwriting recognition; Image segmentation; Jacobian matrices; Robustness; Text recognition; Writing; Word Spotting; directional roses; orientation features;
Conference_Titel :
Content-Based Multimedia Indexing, 2008. CBMI 2008. International Workshop on
Conference_Location :
London
Print_ISBN :
978-1-4244-2043-8
Electronic_ISBN :
978-1-4244-2044-5
DOI :
10.1109/CBMI.2008.4564992