{"title":"基于熵的多语言文档图像文字识别","authors":"Rumaan Bashir, S. Quadri","doi":"10.1109/INDIACOM.2014.6828005","DOIUrl":null,"url":null,"abstract":"Automatic Document Image Analysis has been a prime field of research in the past few decades. Script Identification is an essential part of automatic document image analysis. Script is essentially the text of a written document and languages are written using them. A huge set of techniques have been proposed and many scripts, foreign & domestic, have been identified. But so far, trivial work has been reported for the identification of Kashmiri script. In this paper we are proposing & experimentally testing identification of Kashmiri script collectively with three other related scripts viz. Roman, Devanagri & Urdu using entropy. First, a set of training images are experimented to prepare the knowledge base and later the actual samples have been evaluated. The proposed system offers an accuracy rate of 98.50%.","PeriodicalId":404873,"journal":{"name":"2014 International Conference on Computing for Sustainable Global Development (INDIACom)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Entropy based Script Identification of a multilingual Document Image\",\"authors\":\"Rumaan Bashir, S. Quadri\",\"doi\":\"10.1109/INDIACOM.2014.6828005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automatic Document Image Analysis has been a prime field of research in the past few decades. Script Identification is an essential part of automatic document image analysis. Script is essentially the text of a written document and languages are written using them. A huge set of techniques have been proposed and many scripts, foreign & domestic, have been identified. But so far, trivial work has been reported for the identification of Kashmiri script. In this paper we are proposing & experimentally testing identification of Kashmiri script collectively with three other related scripts viz. Roman, Devanagri & Urdu using entropy. First, a set of training images are experimented to prepare the knowledge base and later the actual samples have been evaluated. The proposed system offers an accuracy rate of 98.50%.\",\"PeriodicalId\":404873,\"journal\":{\"name\":\"2014 International Conference on Computing for Sustainable Global Development (INDIACom)\",\"volume\":\"65 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-03-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Computing for Sustainable Global Development (INDIACom)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/INDIACOM.2014.6828005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Computing for Sustainable Global Development (INDIACom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/INDIACOM.2014.6828005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Entropy based Script Identification of a multilingual Document Image
Automatic Document Image Analysis has been a prime field of research in the past few decades. Script Identification is an essential part of automatic document image analysis. Script is essentially the text of a written document and languages are written using them. A huge set of techniques have been proposed and many scripts, foreign & domestic, have been identified. But so far, trivial work has been reported for the identification of Kashmiri script. In this paper we are proposing & experimentally testing identification of Kashmiri script collectively with three other related scripts viz. Roman, Devanagri & Urdu using entropy. First, a set of training images are experimented to prepare the knowledge base and later the actual samples have been evaluated. The proposed system offers an accuracy rate of 98.50%.