{"title":"历史档案文献手写体与印刷体文本分离的改进","authors":"Mahsa Vafaie, J. Waitelonis, H. Sack","doi":"10.2352/issn.2168-3204.2023.20.1.7","DOIUrl":null,"url":null,"abstract":"The presence of handwritten text and annotations combined with typewritten and machine-printed text in historical archival records make them visually complex, posing challenges for OCR systems in accurately transcribing their content. This paper is an extension of [1], reporting on improvements in the separation of handwritten text from machine-printed text (including typewriters), by the use of FCN-based models trained on datasets created from different data synthesis pipelines. Results show a significant increase of about 20% in the intrinsic evaluation on artificial test sets","PeriodicalId":89080,"journal":{"name":"Archiving : final program and proceedings. IS & T's Archiving Conference","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improvements in Handwritten and Printed Text Separation in Historical Archival Documents\",\"authors\":\"Mahsa Vafaie, J. Waitelonis, H. Sack\",\"doi\":\"10.2352/issn.2168-3204.2023.20.1.7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The presence of handwritten text and annotations combined with typewritten and machine-printed text in historical archival records make them visually complex, posing challenges for OCR systems in accurately transcribing their content. This paper is an extension of [1], reporting on improvements in the separation of handwritten text from machine-printed text (including typewriters), by the use of FCN-based models trained on datasets created from different data synthesis pipelines. Results show a significant increase of about 20% in the intrinsic evaluation on artificial test sets\",\"PeriodicalId\":89080,\"journal\":{\"name\":\"Archiving : final program and proceedings. IS & T's Archiving Conference\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archiving : final program and proceedings. IS & T's Archiving Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2352/issn.2168-3204.2023.20.1.7\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archiving : final program and proceedings. IS & T's Archiving Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2352/issn.2168-3204.2023.20.1.7","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improvements in Handwritten and Printed Text Separation in Historical Archival Documents
The presence of handwritten text and annotations combined with typewritten and machine-printed text in historical archival records make them visually complex, posing challenges for OCR systems in accurately transcribing their content. This paper is an extension of [1], reporting on improvements in the separation of handwritten text from machine-printed text (including typewriters), by the use of FCN-based models trained on datasets created from different data synthesis pipelines. Results show a significant increase of about 20% in the intrinsic evaluation on artificial test sets