{"title":"Off-Line Writer Recognition for Farsi Text","authors":"A. Rafiee, H. Motavalli","doi":"10.1109/MICAI.2007.37","DOIUrl":null,"url":null,"abstract":"A new off-line writer recognition method for Farsi text is presented in this paper. 8 different types of features obtained from the handwritten line of text were considered to identify writers based on theirs handwritten. These features are associated with height and width of text. A typical feed forward neural network was used for classification. This method was applied to 20 writers who wrote 5 to 7 lines and 86.5% recognition rate was obtained.","PeriodicalId":296192,"journal":{"name":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 Sixth Mexican International Conference on Artificial Intelligence, Special Session (MICAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MICAI.2007.37","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
A new off-line writer recognition method for Farsi text is presented in this paper. 8 different types of features obtained from the handwritten line of text were considered to identify writers based on theirs handwritten. These features are associated with height and width of text. A typical feed forward neural network was used for classification. This method was applied to 20 writers who wrote 5 to 7 lines and 86.5% recognition rate was obtained.