Q. Akram, S. Hussain, A. Niazi, Umair Anjum, Faheem Irfan
{"title":"Adapting Tesseract for Complex Scripts: An Example for Urdu Nastalique","authors":"Q. Akram, S. Hussain, A. Niazi, Umair Anjum, Faheem Irfan","doi":"10.1109/DAS.2014.45","DOIUrl":null,"url":null,"abstract":"Tesseract engine supports multilingual text recognition. However, the recognition of cursive scripts using Tesseract is a challenging task. In this paper, Tesseract engine is analyzed and modified for the recognition of Nastalique writing style for Urdu language which is a very complex and cursive writing style of Arabic script. Original Tesseract system has 65.59% and 65.84% accuracies for 14 and 16 font sizes respectively, whereas the modified system, with reduced search space, gives 97.87% and 97.71% accuracies respectively. The efficiency is also improved from an average of 170 milliseconds (ms) to an average of 84 ms for the recognition of Nastalique document images.","PeriodicalId":220495,"journal":{"name":"2014 11th IAPR International Workshop on Document Analysis Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 11th IAPR International Workshop on Document Analysis Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DAS.2014.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 32
Abstract
Tesseract engine supports multilingual text recognition. However, the recognition of cursive scripts using Tesseract is a challenging task. In this paper, Tesseract engine is analyzed and modified for the recognition of Nastalique writing style for Urdu language which is a very complex and cursive writing style of Arabic script. Original Tesseract system has 65.59% and 65.84% accuracies for 14 and 16 font sizes respectively, whereas the modified system, with reduced search space, gives 97.87% and 97.71% accuracies respectively. The efficiency is also improved from an average of 170 milliseconds (ms) to an average of 84 ms for the recognition of Nastalique document images.