{"title":"一种识别大量工程图纸的系统","authors":"Yuhong Yu, A. Samal, S. Seth","doi":"10.1109/ICDAR.1995.602020","DOIUrl":null,"url":null,"abstract":"We present a complete system for recognizing a large class of symbolic engineering drawings that includes flowcharts, chemical plant diagrams, and logic & electrical circuits. The output of the system, a netlist identifying the symbol types and interconnections, may be used for design verification or as a compact portable representation of the drawing. The automatic recognition task is done in two stages: (1) domain-independent rules segment symbols from connection lines in the preprocessed drawing image and (2) an understanding subsystem makes use of a set of domain-specific matchers to classify symbols and correct errors automatically. A graphical user interface is provided to correct residual errors interactively. The system has been tested on a large database of printed images drawn from four different domains.","PeriodicalId":273519,"journal":{"name":"Proceedings of 3rd International Conference on Document Analysis and Recognition","volume":"433 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"93","resultStr":"{\"title\":\"A system for recognizing a large class of engineering drawings\",\"authors\":\"Yuhong Yu, A. Samal, S. Seth\",\"doi\":\"10.1109/ICDAR.1995.602020\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a complete system for recognizing a large class of symbolic engineering drawings that includes flowcharts, chemical plant diagrams, and logic & electrical circuits. The output of the system, a netlist identifying the symbol types and interconnections, may be used for design verification or as a compact portable representation of the drawing. The automatic recognition task is done in two stages: (1) domain-independent rules segment symbols from connection lines in the preprocessed drawing image and (2) an understanding subsystem makes use of a set of domain-specific matchers to classify symbols and correct errors automatically. A graphical user interface is provided to correct residual errors interactively. The system has been tested on a large database of printed images drawn from four different domains.\",\"PeriodicalId\":273519,\"journal\":{\"name\":\"Proceedings of 3rd International Conference on Document Analysis and Recognition\",\"volume\":\"433 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"93\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 3rd International Conference on Document Analysis and Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDAR.1995.602020\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 3rd International Conference on Document Analysis and Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.1995.602020","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A system for recognizing a large class of engineering drawings
We present a complete system for recognizing a large class of symbolic engineering drawings that includes flowcharts, chemical plant diagrams, and logic & electrical circuits. The output of the system, a netlist identifying the symbol types and interconnections, may be used for design verification or as a compact portable representation of the drawing. The automatic recognition task is done in two stages: (1) domain-independent rules segment symbols from connection lines in the preprocessed drawing image and (2) an understanding subsystem makes use of a set of domain-specific matchers to classify symbols and correct errors automatically. A graphical user interface is provided to correct residual errors interactively. The system has been tested on a large database of printed images drawn from four different domains.