Wujiahemaiti Simayi, Mayire Ibrayim, Dilmurat Tursun, A. Hamdulla
{"title":"Research on on-line Uyghur character recognition technology based on center distance feature","authors":"Wujiahemaiti Simayi, Mayire Ibrayim, Dilmurat Tursun, A. Hamdulla","doi":"10.1109/ISSPIT.2013.6781896","DOIUrl":null,"url":null,"abstract":"In this paper, the center distance feature (CDF) is presented as an efficient approach for on-line Uyghur handwritten character recognition. Based on early research for on-line Uyghur handwritten character recognition, a further research is conducted with center distance feature, abbreviated as CDF. This paper introduces the extraction of center distance feature and its three different methods such as CDF-2, CDF-4 and CDF-8 which have improved the average recognition accuracy respectively to 78.17%, 90.47% and 94.50% for the 32 isolated forms of Uyghur characters. 12800 samples from 400 different writers are participated into experiments. The system is trained using 70 percent of total samples and tested on the remained 30 percent.","PeriodicalId":88960,"journal":{"name":"Proceedings of the ... IEEE International Symposium on Signal Processing and Information Technology. IEEE International Symposium on Signal Processing and Information Technology","volume":"15 1 1","pages":"000293-000298"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... IEEE International Symposium on Signal Processing and Information Technology. IEEE International Symposium on Signal Processing and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT.2013.6781896","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
In this paper, the center distance feature (CDF) is presented as an efficient approach for on-line Uyghur handwritten character recognition. Based on early research for on-line Uyghur handwritten character recognition, a further research is conducted with center distance feature, abbreviated as CDF. This paper introduces the extraction of center distance feature and its three different methods such as CDF-2, CDF-4 and CDF-8 which have improved the average recognition accuracy respectively to 78.17%, 90.47% and 94.50% for the 32 isolated forms of Uyghur characters. 12800 samples from 400 different writers are participated into experiments. The system is trained using 70 percent of total samples and tested on the remained 30 percent.