Writer Retrieval and Writer Identification in Greek Papyri

The analysis of digitized historical manuscripts is typically addressed by paleographic experts. Writer identification refers to the classification of known writers while writer retrieval seeks to find the writer by means of image similarity in a dataset of images. While automatic writer identification/retrieval methods already provide promising results for many historical document types, papyri data is very challenging due to the fiber structures and severe artifacts. Thus, an important step for an improved writer identification is the preprocessing and feature sampling process. We investigate several methods and show that a good binarization is key to an improved writer identification in papyri writings. We focus mainly on writer retrieval using unsupervised feature methods based on traditional or self-supervised-based methods. It is, however, also comparable to the state of the art supervised deep learning-based method in the case of writer classification/re-identification.

Legibility Enhancement of Papyri Using Color Processing and Visual Illusions: A Case Study in Critical Vision

Purpose: This article develops theoretical, algorithmic, perceptual, and interaction aspects of script legibility enhancement in the visible light spectrum for the purpose of scholarly editing of papyri texts. - Methods: Novel legibility enhancement algorithms based on color processing and visual illusions are proposed and compared to classic methods. A user experience experiment was carried out to evaluate the solutions and better understand the problem on an empirical basis. - Results: (1) The proposed methods outperformed the comparison methods. (2) The methods that most successfully enhanced script legibility were those that leverage human perception. (3) Users exhibited a broad behavioral spectrum of text-deciphering strategies, under the influence of factors such as personality and social conditioning, tasks and application domains, expertise level and image quality, and affordances of software, hardware, and interfaces. No single method satisfied all factor configurations. Therefore, using synergetically a range of enhancement methods and interaction modalities is suggested for optimal results and user satisfaction. (4) A paradigm of legibility enhancement for critical applications is outlined, comprising the following criteria: interpreting images skeptically; approaching enhancement as a system problem; considering all image structures as potential information; deriving interpretations from connections across distinct spatial locations; and making uncertainty and alternative interpretations explicit, both visually and numerically.