{"title":"一种基于笔画特征的粘合稿财经汉字分割算法","authors":"Zili Li, Peng Wang","doi":"10.1109/PACIIA.2008.340","DOIUrl":null,"url":null,"abstract":"In electronic commerce and the infomationization of finance, the recognition of manuscript financial Chinese characters by means of computer is a realm of significance and challenge. The key in this realm is the segmentation of the image of Chinese characters correctly and efficiently. Among the existing methods, ones which is of high correctness and efficiency are rare. In this paper, starting with analysis the character of manuscript financial Chinese characters, an algorithm is found to segment conglutinate manuscript financial Chinese characters based on the character of stroke. Many experiments prove that this algorithm has a greater advantage than others.","PeriodicalId":275193,"journal":{"name":"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Algorithm for Segmentation of Conglutinate Manuscript Financial Chinese Characters Based on the Character of Stroke\",\"authors\":\"Zili Li, Peng Wang\",\"doi\":\"10.1109/PACIIA.2008.340\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In electronic commerce and the infomationization of finance, the recognition of manuscript financial Chinese characters by means of computer is a realm of significance and challenge. The key in this realm is the segmentation of the image of Chinese characters correctly and efficiently. Among the existing methods, ones which is of high correctness and efficiency are rare. In this paper, starting with analysis the character of manuscript financial Chinese characters, an algorithm is found to segment conglutinate manuscript financial Chinese characters based on the character of stroke. Many experiments prove that this algorithm has a greater advantage than others.\",\"PeriodicalId\":275193,\"journal\":{\"name\":\"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PACIIA.2008.340\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PACIIA.2008.340","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Algorithm for Segmentation of Conglutinate Manuscript Financial Chinese Characters Based on the Character of Stroke
In electronic commerce and the infomationization of finance, the recognition of manuscript financial Chinese characters by means of computer is a realm of significance and challenge. The key in this realm is the segmentation of the image of Chinese characters correctly and efficiently. Among the existing methods, ones which is of high correctness and efficiency are rare. In this paper, starting with analysis the character of manuscript financial Chinese characters, an algorithm is found to segment conglutinate manuscript financial Chinese characters based on the character of stroke. Many experiments prove that this algorithm has a greater advantage than others.