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Automatic Handwritten Character Segmentation for Paleographical Character Shape Analysis

Abstract : Written texts are both abstract and physical objects: ideas, signs and shapes, whose meanings, graphical systems and social connotations evolve through time. To study this dual nature of texts, paleographers need to analyse large scale corpora at the finest granularity, such as character shape. This goal can only be reached through an automatic segmentation process. In this paper, we present a method, based on Handwritten Text Recognition, to automatically align images of digitized manuscripts with texts from scholarly editions, at the levels of page, column, line, word, and character. It has been successfully applied to two datasets of medieval manuscripts, which are now almost fully segmented at character level. The quality of the word and character segmentations are evaluated and further paleographical analysis are presented.
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Contributor : Dominique Stutzmann <>
Submitted on : Tuesday, December 31, 2019 - 8:33:40 AM
Last modification on : Wednesday, September 16, 2020 - 5:35:44 PM



Théodore Bluche, Dominique Stutzmann, Christopher Kermorvant. Automatic Handwritten Character Segmentation for Paleographical Character Shape Analysis. 2016 12th IAPR Workshop on Document Analysis Systems (DAS), Apr 2016, Santorini, France. pp.42-47, ⟨10.1109/DAS.2016.74⟩. ⟨hal-02425715⟩



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