Advertisement

A Method for Scribe Distinction in Medieval Manuscripts Using Page Layout Features

  • Claudio De Stefano
  • Francesco Fontanella
  • Marilena Maniaci
  • Alessandra Scotto di Freca
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6978)

Abstract

In the framework of Palaeography, the use of digital image processing techniques has received increasing attention in recent years, resulting in a new research field commonly denoted as “digital palaeography”. In such a field, a key role is played by both pattern recognition and feature extraction methods, which provide quantitative arguments for supporting expert deductions. In this paper, we present a pattern recognition system which tries to solve a typical palaeographic problem: to distinguish the different scribes who have worked together to the transcription of a single medieval book. In the specific case of a high standardized book typology (the so called Latin “Giant Bible”), we wished to verify if the extraction of certain specifically devised features, concerning the layout of the page, allowed to obtain satisfactory results. To this aim, we have also performed a statistical analysis of the considered features in order to characterize their discriminant power. The experiments, performed on a large dataset of digital images from the so called “Avila Bible” - a giant Latin copy of the whole Bible produced during the XII century between Italy and Spain - confirmed the effectiveness of the proposed method.

Keywords

Recognition Rate Information Gain Feature Subset Multi Layer Perceptron Univariate Measure 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Black, D.: The Theory of Committees and Elections, 2nd edn. Cambridge University Press, London (1963)zbMATHGoogle Scholar
  2. 2.
    Bozzolo, C., Coq, D., Muzerelle, D., Ornato, E.: Noir et blanc. premiers résultats d’une enquête sur la mise en page dans le livre médiéval. In: Il libro e il testo, Urbino, pp. 195–221 (1982)Google Scholar
  3. 3.
    Ciula, A.: The palaeographical method under the light of a digital approach. In: Kodikologie und Paläographie im digitalen Zeitalter-Codicology and Palaeography in the Digital Age, pp. 219–237 (2009)Google Scholar
  4. 4.
    Gurrado, M.: “graphoshop”, uno strumento informatico per l’analisi paleografica quantitativa. In: Rehbein, M., Sahle, P., Schaßan, T. (eds.) Kodikologie und Paläographie im digitalen Zeitalter / Codicology and Palaeography in the Digital Age, pp. 251–259 (2009)Google Scholar
  5. 5.
    Hall, M.: Correlation-based Feature Selection for Machine Learning. Ph.D. thesis, University of Waikato (1999)Google Scholar
  6. 6.
    Kononenko, I.: Estimating Attributes: Analysis and Extensions of RELIEF. In: European Conference on Machine Learning, pp. 171–182 (1994)Google Scholar
  7. 7.
    Liu, H., Setiono, R.: Chi2: Feature Selection and Discretization of Numeric Attributes. In: ICTAI, pp. 88–91. IEEE Computer Society, Los Alamitos (1995)Google Scholar
  8. 8.
    Maniaci, M., Ornato, G.: Prime considerazioni sulla genesi e la storia della bibbia di avila. Miscellanea F. Magistrale, Spoleto (2010) (in press)Google Scholar
  9. 9.
    Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann Series in Machine Learning. Morgan Kaufmann, San Francisco (1993)Google Scholar
  10. 10.
    Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning representations by back-propagating errors. Nature 323(9), 533–536 (1986)CrossRefzbMATHGoogle Scholar
  11. 11.
    Stokes, P.: Computer-aided palaeography, present and future. In: Rehbein, M., Sahle, P., Schaßan, T. (eds.) Kodikologie und Paläographie im digitalen Zeitalter / Codicology and Palaeography in the Digital Age. pp. 309–338 (2009)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Claudio De Stefano
    • 1
  • Francesco Fontanella
    • 1
  • Marilena Maniaci
    • 2
  • Alessandra Scotto di Freca
    • 1
  1. 1.Dipartimento di Automazione, ElettromagnetismoIngegneria dell’Informazione e Matematica IndustrialeCassinoItaly
  2. 2.Dipartimento di Filologia e StoriaUniversity of CassinoCassinoItaly

Personalised recommendations