{"title":"中世纪文献的自动笔迹识别","authors":"M. Bulacu, Lambert Schomaker","doi":"10.1109/ICIAP.2007.33","DOIUrl":null,"url":null,"abstract":"In this paper, we evaluate the performance of text- independent writer identification methods on a handwriting dataset containing medieval English documents. Applicable identification rates are achieved by combining textural features (joint directional probability distributions) with allographic features (grapheme-emission distributions). The aim is to develop an automatic handwriting identification tool that can assist the paleographer in the task of determining the authorship of historical manuscripts.","PeriodicalId":118466,"journal":{"name":"14th International Conference on Image Analysis and Processing (ICIAP 2007)","volume":"336 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"50","resultStr":"{\"title\":\"Automatic Handwriting Identification on Medieval Documents\",\"authors\":\"M. Bulacu, Lambert Schomaker\",\"doi\":\"10.1109/ICIAP.2007.33\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we evaluate the performance of text- independent writer identification methods on a handwriting dataset containing medieval English documents. Applicable identification rates are achieved by combining textural features (joint directional probability distributions) with allographic features (grapheme-emission distributions). The aim is to develop an automatic handwriting identification tool that can assist the paleographer in the task of determining the authorship of historical manuscripts.\",\"PeriodicalId\":118466,\"journal\":{\"name\":\"14th International Conference on Image Analysis and Processing (ICIAP 2007)\",\"volume\":\"336 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"50\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"14th International Conference on Image Analysis and Processing (ICIAP 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIAP.2007.33\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"14th International Conference on Image Analysis and Processing (ICIAP 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIAP.2007.33","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic Handwriting Identification on Medieval Documents
In this paper, we evaluate the performance of text- independent writer identification methods on a handwriting dataset containing medieval English documents. Applicable identification rates are achieved by combining textural features (joint directional probability distributions) with allographic features (grapheme-emission distributions). The aim is to develop an automatic handwriting identification tool that can assist the paleographer in the task of determining the authorship of historical manuscripts.
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