{"title":"Font recognition using Variogram fractal dimension","authors":"A. Hajiannezhad, S. Mozaffari","doi":"10.1109/IRANIANCEE.2012.6292432","DOIUrl":null,"url":null,"abstract":"This paper is dealing with font recognition problem in Farsi, Arabic, and English documents. It considers font recognition as texture identification task and the extracted features are independent of document content. The proposed method is based on one of the fractal dimension techniques which is called Variogram Analysis. The average recognition rates using RBF, and KNN classifiers are respectively %95.5, %96 for Farsi fonts, and % 96.9, %98.84 for Arabic fonts, and % 98.21, %99.6 for English fonts. The most important advantages of our algorithm are low feature dimensions, low computational complexity, and high speed compared with the previous efforts.","PeriodicalId":308726,"journal":{"name":"20th Iranian Conference on Electrical Engineering (ICEE2012)","volume":"33 5","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"20th Iranian Conference on Electrical Engineering (ICEE2012)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IRANIANCEE.2012.6292432","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
This paper is dealing with font recognition problem in Farsi, Arabic, and English documents. It considers font recognition as texture identification task and the extracted features are independent of document content. The proposed method is based on one of the fractal dimension techniques which is called Variogram Analysis. The average recognition rates using RBF, and KNN classifiers are respectively %95.5, %96 for Farsi fonts, and % 96.9, %98.84 for Arabic fonts, and % 98.21, %99.6 for English fonts. The most important advantages of our algorithm are low feature dimensions, low computational complexity, and high speed compared with the previous efforts.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
