{"title":"基于遗传算法的笔画匹配方法","authors":"Hao Bai, Xiwen Zhang","doi":"10.1109/SIPROCESS.2016.7888284","DOIUrl":null,"url":null,"abstract":"It is natural way to write Chinese characters by digital pen for foreign students, whose handwriting information is much richer than digital image. Stroke matching is the prerequisite to analyze handwriting errors of Chinese character. Present research hardly delivers the optimal solution of the problem on the growing sizes and complexity because of wide differences among learners' writing qualities and features. This paper proposes an approach based on genetic algorithm to match strokes. Construction of fitness function considers structural and writing features of Chinese characters. The method can achieve correct matching stroke rate 90.17% at least in the experiments, which indicates that our proposed approach Is effective In next steps of handwriting errors analysis.","PeriodicalId":142802,"journal":{"name":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"A method of matching strokes based on genetic algorithm\",\"authors\":\"Hao Bai, Xiwen Zhang\",\"doi\":\"10.1109/SIPROCESS.2016.7888284\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is natural way to write Chinese characters by digital pen for foreign students, whose handwriting information is much richer than digital image. Stroke matching is the prerequisite to analyze handwriting errors of Chinese character. Present research hardly delivers the optimal solution of the problem on the growing sizes and complexity because of wide differences among learners' writing qualities and features. This paper proposes an approach based on genetic algorithm to match strokes. Construction of fitness function considers structural and writing features of Chinese characters. The method can achieve correct matching stroke rate 90.17% at least in the experiments, which indicates that our proposed approach Is effective In next steps of handwriting errors analysis.\",\"PeriodicalId\":142802,\"journal\":{\"name\":\"2016 IEEE International Conference on Signal and Image Processing (ICSIP)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Signal and Image Processing (ICSIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SIPROCESS.2016.7888284\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Signal and Image Processing (ICSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIPROCESS.2016.7888284","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A method of matching strokes based on genetic algorithm
It is natural way to write Chinese characters by digital pen for foreign students, whose handwriting information is much richer than digital image. Stroke matching is the prerequisite to analyze handwriting errors of Chinese character. Present research hardly delivers the optimal solution of the problem on the growing sizes and complexity because of wide differences among learners' writing qualities and features. This paper proposes an approach based on genetic algorithm to match strokes. Construction of fitness function considers structural and writing features of Chinese characters. The method can achieve correct matching stroke rate 90.17% at least in the experiments, which indicates that our proposed approach Is effective In next steps of handwriting errors analysis.