Identifying the writer of ancient inscriptions and Byzantine codices. A novel approach

  • Authors:

  • C. Papaodysseus;P. Rousopoulos;F. Giannopoulos;S. Zannos;D. Arabadjis;M. Panagopoulos;E. Kalfa;C. Blackwell;S. Tracy

  • Affiliations:

  • National Technical University of Athens, Department of Electrical and Computer Engineering, 9 Heroon Polytechneiou, GR-15773 Athens, Greece;Technical Institute of Chalkida, Department of Automatic Control, Chalkida, Euboea, Greece;National Technical University of Athens, Department of Electrical and Computer Engineering, 9 Heroon Polytechneiou, GR-15773 Athens, Greece;National Technical University of Athens, Department of Electrical and Computer Engineering, 9 Heroon Polytechneiou, GR-15773 Athens, Greece;National Technical University of Athens, Department of Electrical and Computer Engineering, 9 Heroon Polytechneiou, GR-15773 Athens, Greece;Ionian University, Department of Music Studies, Corfu, Greece;National Technical University of Athens, Department of Electrical and Computer Engineering, 9 Heroon Polytechneiou, GR-15773 Athens, Greece;Furman University, Department of Classics, Greenville, SC, USA;Institute for Advanced Study, School of Historical Studies, Princeton, NJ, USA

  • Venue:
  • Computer Vision and Image Understanding
  • Year:
  • 2014

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Abstract

In this paper, a novel methodology is presented aiming at the automatic identification of the writer of ancient inscriptions and Byzantine codices. This identification can offer unambiguous dating of these ancient manuscripts. The introduced methodology is also applicable to contours of complexes of letters or any class of similar curves. The method presented here initially estimates the normalized curvature at each pixel of a letter contour. Subsequently, it performs pair-wise comparisons of the curvatures sequences that correspond to two realizations of the same alphabet symbol. Then, it introduces a new Proposition that, on the basis of the previous results, offers a closed solution to the problem of matching two equinumerous digital contours in the Least Squares sense. Next, a criterion is employed quantifying the similarity of two realizations of the same alphabet symbol. Finally, a number of statistical criteria are introduced for the automatic identification of the writer of ancient manuscripts. The introduced method did not employ any reference manuscript neither the number of distinct hands who had written the considered set of manuscripts nor any related information whatsoever; it also performs quite efficiently even if a small number of realizations (less than 6) of certain alphabet symbols appear in a tested document. The only a priori knowledge is the alphabet of the language under consideration. We would like to stress that otherwise the method does not depend at all on the language itself. Namely it does not take into account if the alphabet is Latin, Greek, Etruscan, etc. The methodology and the related, developed information system has been applied to 46 ancient inscriptions of the Classical and Hellenistic era and 23 Byzantine codices, offering 100% accurate results, in the sense that the obtained results are in full agreement with prominent scholars in the field of Archaeology, History and Classical Studies.