Writer Retrieval And Writer Identification In Greek Papyri

Abstract

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 While automatic writer identification/retrieval methods already provide promising results for many historical document types, papyri data is very challenging due to the fiber structures and severe artifacts.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.

Stats

• citations13
• S2 citations—
• github stars0
• HF likes0
• heat score8.60
• arxiv keychristlein2022writer

Related papers

• Feature Mixing For Writer Retrieval And Identification On Papyri Fragments (2023)7.16
• Re-ranking For Writer Identification And Writer Retrieval (2020)7.81
• Writer Identification And Writer Retrieval Based On Netvlad With Re-ranking (2020)8.82
• ICDAR 2019 Competition On Image Retrieval For Historical Handwritten Documents (2019)11.29
• SAGHOG: Self-supervised Autoencoder For Generating HOG Features For Writer Retrieval (2024)4.52
• Explainable Coarse-to-fine Ancient Manuscript Duplicates Discovery (2025)1.56
• Self-supervised Vision Transformers For Writer Retrieval (2024)5.24
• Online Writer Retrieval With Chinese Handwritten Phrases: A Synergistic Temporal-frequency Representation Learning Approach (2024)7.11