C4.5: programs for machine learning
C4.5: programs for machine learning
Estimating attributes: analysis and extensions of RELIEF
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Chi2: Feature Selection and Discretization of Numeric Attributes
TAI '95 Proceedings of the Seventh International Conference on Tools with Artificial Intelligence
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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.