P. Banerjee, Supriya Das, B. Seraogi, Himadri Majumdar, Srinivas Mukkamala, Rahul Roy, B. Chaudhuri
{"title":"Automatic Elevation Datum Detection and Hyperlinking of Architecture, Engineering & Construction Documents","authors":"P. Banerjee, Supriya Das, B. Seraogi, Himadri Majumdar, Srinivas Mukkamala, Rahul Roy, B. Chaudhuri","doi":"10.1109/ICDAR.2017.266","DOIUrl":null,"url":null,"abstract":"In AEC (Architecture, Engineering & Construction) industry drawing documents are used as a blueprint to facilitate the construction process. It is also a graphical language that communicates ideas and information from one mind to another. A construction project normally contains huge number of such drawing documents. An engineer or architect often needs to refer different documents while drawing a new one or marking some irregularity or real construction. Elevation datum is one of the graphical representation for referring one document to another. It will be a very difficult and time-consuming task manually to identify elevation datum and link a file with respect to each datum. Our suggested method is aimed to overcome this hurdle. Therefore, the proposed system will automatically find the elevation datums from the existing drawing documents and will also create hyperlinks to enable the engineer to quickly navigate among the drawing files. We have achieved overall accuracy of 95.28% for elevation datum detection and accurate destination document text recognition.","PeriodicalId":433676,"journal":{"name":"2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)","volume":"432 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.2017.266","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In AEC (Architecture, Engineering & Construction) industry drawing documents are used as a blueprint to facilitate the construction process. It is also a graphical language that communicates ideas and information from one mind to another. A construction project normally contains huge number of such drawing documents. An engineer or architect often needs to refer different documents while drawing a new one or marking some irregularity or real construction. Elevation datum is one of the graphical representation for referring one document to another. It will be a very difficult and time-consuming task manually to identify elevation datum and link a file with respect to each datum. Our suggested method is aimed to overcome this hurdle. Therefore, the proposed system will automatically find the elevation datums from the existing drawing documents and will also create hyperlinks to enable the engineer to quickly navigate among the drawing files. We have achieved overall accuracy of 95.28% for elevation datum detection and accurate destination document text recognition.