Vom Zeichen zur Schrift: Mit Mustererkennung zur automatisierten Schreiberhanderkennung in mittelalterlichen und frühneuzeitlichen Handschriften

Abstract

For Digital Humanities in medieval studies and early modern studies, the digitization of manuscripts is a central field. Since each manuscript displays its own unique characteristics, the automatic generation of a machine-readable text using Optical Character Recognition (OCR) as applied to digital images leads, in most cases, to error-prone results. However, characteristics of handwriting such as the size of letters and spacing, slope, and so on can be used to identify the scribe or scribes. This paper demonstrates how the analysis of manuscript images can be used to identify the scribe or scribes. An algorithym will support additional paleographic and codicological findings and provide evidence for the verification or falsification of uncertain attributions.

Keywords

• mustererkennung
• automatische klassifikation
• handschrift (grafologie)