{"title":"Document table detection and analysis using projection scale space","authors":"L. I. Kalyon, Y. S. Akgul","doi":"10.1109/SIU.2014.6830480","DOIUrl":null,"url":null,"abstract":"Detection and analysis of tables on document images has been one of the most researched topics in document image processing. In this study, we define novel methods for the detection and analysis of tables from document images, and show their performance results on realistic table examples. The main method developed is projection-scale-space (PSS), where local and global constraints of the table in row basis are analyzed for consistency. PSS is robust to the character set used in a document, the image resolution and the noise ratio of a document image, and can perform detection operations in a highly effective manner. Furthermore, the method proposed works on tables with and without table borders and is able to analyze rows and columns of tables. The proposed method has been tested on a dataset of 105 documents containing 130 tables and the systems high performance has been stated in quantitative basis.","PeriodicalId":384835,"journal":{"name":"2014 22nd Signal Processing and Communications Applications Conference (SIU)","volume":"81 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 22nd Signal Processing and Communications Applications Conference (SIU)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIU.2014.6830480","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
Detection and analysis of tables on document images has been one of the most researched topics in document image processing. In this study, we define novel methods for the detection and analysis of tables from document images, and show their performance results on realistic table examples. The main method developed is projection-scale-space (PSS), where local and global constraints of the table in row basis are analyzed for consistency. PSS is robust to the character set used in a document, the image resolution and the noise ratio of a document image, and can perform detection operations in a highly effective manner. Furthermore, the method proposed works on tables with and without table borders and is able to analyze rows and columns of tables. The proposed method has been tested on a dataset of 105 documents containing 130 tables and the systems high performance has been stated in quantitative basis.