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Revealing the visually unknown in ancient manuscripts with a similarity measure for IR-imaged inks

Licata, Aaron and Psarrou, Alexandra and Kokla, Vassiliki (2009) Revealing the visually unknown in ancient manuscripts with a similarity measure for IR-imaged inks. In: Proceedings of the 10th International Conference on Document Analysis and Recognition: ICDAR 2009. 26 - 29 July 2009, Barcelona, Catalonia, Spain. IEEE, pp. 818-822. ISBN 9781424445004

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Official URL: http://dx.doi.org/10.1109/ICDAR.2009.49

Abstract

One of the tasks facing historians and conservationists is the authentication or dating of medieval manuscripts. To this end it is important to them to verify whether writings on the same or different manuscripts are concurrent. In this work we explore this task by capturing images of manuscript pages in infrared (IR) and modelling and then comparing the ink appearance of segmented text. The modelling of the text appearance relies on the unsupervised multimodal clustering of ink descriptors and the derived probability density functions. The similarity measure is built around the distribution of cluster labels and their proportions. We demonstrate our method by using both model inks of known composition and authentic Byzantine manuscripts.

Item Type:Book Section
Research Community:University of Westminster > Electronics and Computer Science, School of
ID Code:7254
Deposited On:14 Jan 2010 15:41
Last Modified:17 Jul 2013 11:26

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