Ege Şendoğan , Victoria Eyharabide , Béatrice Caseau , Isabelle Bloch
{"title":"Automatic characterization of the border deterioration in Byzantine seals","authors":"Ege Şendoğan , Victoria Eyharabide , Béatrice Caseau , Isabelle Bloch","doi":"10.1016/j.daach.2025.e00410","DOIUrl":null,"url":null,"abstract":"<div><div>Byzantine seals were attached to official documents to authenticate the sender, thus enclosing a valuable part of the Byzantine Empire’s history. With the aim to provide computational models to help historians in the seal interpretation, this paper proposes a method to automatically determine the level of deterioration of the seal borders from their photographs, i.e., a non-destructive inspection. The method consists of a segmentation step based on Morphological Geodesic Active Contours, a feature extraction step, and a classification step that groups the seals into four border deterioration categories. Our best results reached 0.80 in accuracy, 0.73 in Cohen’s Kappa statistics score, and 0.80 in the macro F1 score.</div></div>","PeriodicalId":38225,"journal":{"name":"Digital Applications in Archaeology and Cultural Heritage","volume":"37 ","pages":"Article e00410"},"PeriodicalIF":0.0000,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Digital Applications in Archaeology and Cultural Heritage","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2212054825000128","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Byzantine seals were attached to official documents to authenticate the sender, thus enclosing a valuable part of the Byzantine Empire’s history. With the aim to provide computational models to help historians in the seal interpretation, this paper proposes a method to automatically determine the level of deterioration of the seal borders from their photographs, i.e., a non-destructive inspection. The method consists of a segmentation step based on Morphological Geodesic Active Contours, a feature extraction step, and a classification step that groups the seals into four border deterioration categories. Our best results reached 0.80 in accuracy, 0.73 in Cohen’s Kappa statistics score, and 0.80 in the macro F1 score.