Medical document reader on Android smartphone

Arrart Kongtaln, Sutthipong Minsakorn, Lalita Yodchaloemkul, Sirasit Boontarak, S. Phongsuphap
{"title":"Medical document reader on Android smartphone","authors":"Arrart Kongtaln, Sutthipong Minsakorn, Lalita Yodchaloemkul, Sirasit Boontarak, S. Phongsuphap","doi":"10.1109/ICT-ISPC.2014.6923219","DOIUrl":null,"url":null,"abstract":"This paper presents a method for reading medical documents by using an Android smartphone. We have used techniques based on the Tesseract OCR Engine to extract the text content from medical document images such as a physical examination report. The following factors related to the document are considered: character font, text block size, and distance between the document and the camera on the phone. Based on experimental results, we found that among three character fonts (Angsana New, Calibri, and Tahoma), Calibri and Tahoma gave very high average accuracies (greater than 90%) for both character recognition and word recognition, but Angsana New gave quite a lower accuracy, about 75%. For the optimal distance between the document and the smartphone, the recommended distance is from 12 cm. to 15 cm. for a document block size of 21 × 3, 13 × 10, 12 × 8, or 10 × 13 cm2.","PeriodicalId":300460,"journal":{"name":"2014 Third ICT International Student Project Conference (ICT-ISPC)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Third ICT International Student Project Conference (ICT-ISPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICT-ISPC.2014.6923219","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

This paper presents a method for reading medical documents by using an Android smartphone. We have used techniques based on the Tesseract OCR Engine to extract the text content from medical document images such as a physical examination report. The following factors related to the document are considered: character font, text block size, and distance between the document and the camera on the phone. Based on experimental results, we found that among three character fonts (Angsana New, Calibri, and Tahoma), Calibri and Tahoma gave very high average accuracies (greater than 90%) for both character recognition and word recognition, but Angsana New gave quite a lower accuracy, about 75%. For the optimal distance between the document and the smartphone, the recommended distance is from 12 cm. to 15 cm. for a document block size of 21 × 3, 13 × 10, 12 × 8, or 10 × 13 cm2.
安卓智能手机上的医疗文件阅读器
本文介绍了一种使用Android智能手机阅读医疗文件的方法。我们使用基于Tesseract OCR引擎的技术从医学文档图像(如体检报告)中提取文本内容。考虑以下与文档相关的因素:字符字体,文本块大小以及文档与手机上的相机之间的距离。基于实验结果,我们发现在三种字符字体(Angsana New, Calibri和Tahoma)中,Calibri和Tahoma在字符识别和单词识别方面的平均准确率都很高(大于90%),而Angsana New的准确率相当低,约为75%。文档与智能手机之间的最佳距离建议为12cm。到15厘米。对于文档块大小为21 × 3、13 × 10、12 × 8或10 × 13 cm2的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信