{"title":"Isolated vietnamese handwriting recognition embedded system applied combined feature extraction method","authors":"T. T. Van, Phi Nguyen Huu, Trang Hoang","doi":"10.1109/ATC.2015.7388375","DOIUrl":null,"url":null,"abstract":"In this research, an embedded system approaching isolated Vietnamese handwriting upper case recognition is illustrated. Obtained results from experiments have experienced that proposed feature extraction method, a major step of complete character recognition scheme, combining contour profile and projection histogram techniques is superior to others. Furthermore, the full conceptual system performance is evaluated on the embedded system, namely BeagleBoard-xM board, to confirm that recognition probability is up to more 90% over 27000 characters over thirty different persons.","PeriodicalId":142783,"journal":{"name":"2015 International Conference on Advanced Technologies for Communications (ATC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Advanced Technologies for Communications (ATC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ATC.2015.7388375","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 this research, an embedded system approaching isolated Vietnamese handwriting upper case recognition is illustrated. Obtained results from experiments have experienced that proposed feature extraction method, a major step of complete character recognition scheme, combining contour profile and projection histogram techniques is superior to others. Furthermore, the full conceptual system performance is evaluated on the embedded system, namely BeagleBoard-xM board, to confirm that recognition probability is up to more 90% over 27000 characters over thirty different persons.