Niranjan S. Ka, Vijaya Kumarb, Hemantha Kumar, Manjunath Aradhya
{"title":"FLD Based Unconstrained Handwritten Kannada Character Recognition","authors":"Niranjan S. Ka, Vijaya Kumarb, Hemantha Kumar, Manjunath Aradhya","doi":"10.1109/FGCNS.2008.17","DOIUrl":null,"url":null,"abstract":"In this paper, we propose unconstrained handwritten Kannada character recognition based on Fisher linear discriminant analysis (FLD). The proposed system extracts features from well known FLD, Two dimensional FLD (2D-FLD) and diagonal FLD. In order to classify the characters, we explore different distance measure techniques and compare their results. The proposed system is tested on unconstrained handwritten Kannada characters with pertaining to large number of character classes. The system showed effectiveness and feasibility of the proposed method.","PeriodicalId":370780,"journal":{"name":"2008 Second International Conference on Future Generation Communication and Networking Symposia","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"31","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 Second International Conference on Future Generation Communication and Networking Symposia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FGCNS.2008.17","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 31
Abstract
In this paper, we propose unconstrained handwritten Kannada character recognition based on Fisher linear discriminant analysis (FLD). The proposed system extracts features from well known FLD, Two dimensional FLD (2D-FLD) and diagonal FLD. In order to classify the characters, we explore different distance measure techniques and compare their results. The proposed system is tested on unconstrained handwritten Kannada characters with pertaining to large number of character classes. The system showed effectiveness and feasibility of the proposed method.