Walaa Aly, S. Uchida, Akio Fujiyoshi, Masakazu Suzuki
{"title":"数学符号间空间关系的统计分类","authors":"Walaa Aly, S. Uchida, Akio Fujiyoshi, Masakazu Suzuki","doi":"10.1109/ICDAR.2009.90","DOIUrl":null,"url":null,"abstract":"In this paper, a statistical decision method for automatic classification of spatial relationships between each adjacent pair is proposed. Each pair is composed of mathematical symbols and/or alphabetical characters. Special treatment of mathematical symbols with variable size is important.This classification is important to recognize an accurate structure analysis module of math OCR. Experimental results on a very large database showed that the proposed method worked well with an accuracy of 99.57% by two important geometric feature relative size and relative position.","PeriodicalId":433762,"journal":{"name":"2009 10th International Conference on Document Analysis and Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Statistical Classification of Spatial Relationships among Mathematical Symbols\",\"authors\":\"Walaa Aly, S. Uchida, Akio Fujiyoshi, Masakazu Suzuki\",\"doi\":\"10.1109/ICDAR.2009.90\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a statistical decision method for automatic classification of spatial relationships between each adjacent pair is proposed. Each pair is composed of mathematical symbols and/or alphabetical characters. Special treatment of mathematical symbols with variable size is important.This classification is important to recognize an accurate structure analysis module of math OCR. Experimental results on a very large database showed that the proposed method worked well with an accuracy of 99.57% by two important geometric feature relative size and relative position.\",\"PeriodicalId\":433762,\"journal\":{\"name\":\"2009 10th International Conference on Document Analysis and Recognition\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 10th International Conference on Document Analysis and Recognition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDAR.2009.90\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 10th International Conference on Document Analysis and Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.2009.90","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical Classification of Spatial Relationships among Mathematical Symbols
In this paper, a statistical decision method for automatic classification of spatial relationships between each adjacent pair is proposed. Each pair is composed of mathematical symbols and/or alphabetical characters. Special treatment of mathematical symbols with variable size is important.This classification is important to recognize an accurate structure analysis module of math OCR. Experimental results on a very large database showed that the proposed method worked well with an accuracy of 99.57% by two important geometric feature relative size and relative position.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
