{"title":"字符结构信息在在线手写维吾尔文字识别中的应用","authors":"Yidayet Zaydun, Tsuyoshi Saitoh","doi":"10.11371/IIEEJ.37.244","DOIUrl":null,"url":null,"abstract":"〈Summary〉 This paper discusses the use of structure information of Uyghur characters as a feature in online handwriting recognition on portable digital devices. Based on the position of secondary stroke, Uyghur characters can be separating into 4 groups. In this case, the unknown input character compares to other characters in its corresponding group only. This will be shortening the comparison time. The experiment result of freely-written 10 dataset showed that, the comparison time is reduced by 64.32% while the recognition rate improved 5.87%. The Approximate Stroke Sequence String Matching method is applied to Uyghur handwriting character recognition and an average recognition rate of 93.95% is obtained. It is improved to 96.6% while using the structure information of handwritten characters. Based on these results we discuss that, the recognition rate will be improved by the using of some other features like character frequency, the number of secondary strokes, and other.","PeriodicalId":153591,"journal":{"name":"The Journal of the Institute of Image Electronics Engineers of Japan","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Application of Character Structure Information in Online Handwriting Uyghur Character Recognition\",\"authors\":\"Yidayet Zaydun, Tsuyoshi Saitoh\",\"doi\":\"10.11371/IIEEJ.37.244\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"〈Summary〉 This paper discusses the use of structure information of Uyghur characters as a feature in online handwriting recognition on portable digital devices. Based on the position of secondary stroke, Uyghur characters can be separating into 4 groups. In this case, the unknown input character compares to other characters in its corresponding group only. This will be shortening the comparison time. The experiment result of freely-written 10 dataset showed that, the comparison time is reduced by 64.32% while the recognition rate improved 5.87%. The Approximate Stroke Sequence String Matching method is applied to Uyghur handwriting character recognition and an average recognition rate of 93.95% is obtained. It is improved to 96.6% while using the structure information of handwritten characters. Based on these results we discuss that, the recognition rate will be improved by the using of some other features like character frequency, the number of secondary strokes, and other.\",\"PeriodicalId\":153591,\"journal\":{\"name\":\"The Journal of the Institute of Image Electronics Engineers of Japan\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The Journal of the Institute of Image Electronics Engineers of Japan\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.11371/IIEEJ.37.244\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Journal of the Institute of Image Electronics Engineers of Japan","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.11371/IIEEJ.37.244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Application of Character Structure Information in Online Handwriting Uyghur Character Recognition
〈Summary〉 This paper discusses the use of structure information of Uyghur characters as a feature in online handwriting recognition on portable digital devices. Based on the position of secondary stroke, Uyghur characters can be separating into 4 groups. In this case, the unknown input character compares to other characters in its corresponding group only. This will be shortening the comparison time. The experiment result of freely-written 10 dataset showed that, the comparison time is reduced by 64.32% while the recognition rate improved 5.87%. The Approximate Stroke Sequence String Matching method is applied to Uyghur handwriting character recognition and an average recognition rate of 93.95% is obtained. It is improved to 96.6% while using the structure information of handwritten characters. Based on these results we discuss that, the recognition rate will be improved by the using of some other features like character frequency, the number of secondary strokes, and other.