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Local orientation extraction for Wordspotting in Syriac manuscripts

Petra Bilane 1 Stéphane Bres 1 Hubert Emptoz 1
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
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 45°. 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.
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Submitted on : Thursday, April 27, 2017 - 5:01:21 PM
Last modification on : Wednesday, July 8, 2020 - 12:43:46 PM

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Petra Bilane, Stéphane Bres, Hubert Emptoz. Local orientation extraction for Wordspotting in Syriac manuscripts. International Conference on Image and Signal Processing (ICISP 08), Jul 2008, Cherbourg-Octeville, France. pp.481-489, ⟨10.1007/978-3-540-69905-7_55⟩. ⟨hal-01515579⟩



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