Implementation of OCR (Optical Character Recognition) Using Tesseract in Detecting Character in Quotes Text Images

Q3 Engineering
Ikha Novie Tri Lestari, Dadang Iskandar Mulyana
{"title":"Implementation of OCR (Optical Character Recognition) Using Tesseract in Detecting Character in Quotes Text Images","authors":"Ikha Novie Tri Lestari, Dadang Iskandar Mulyana","doi":"10.37385/jaets.v4i1.905","DOIUrl":null,"url":null,"abstract":"The development of technology in Indonesia is currently increasingly advanced in people's lives and cannot be avoided. The use of Artificial Intelligence in helping humans in dealing with problems is growing. Humans can take advantage of computer/smartphone media in today's technological era. One of its uses is Optical Character Recognition. This research is motivated by the problem where the running system requires development in terms of technology to detect characters in the quote text image, because the previous system still performs manual input. Optical Character Recognition has been widely used to extract characters contained in digital image media. The ability of OCR methods and techniques is very dependent on the normalization process as an initial process before entering into the next stages such as segmentation and identification. The image normalization process aims to obtain a better input image so that the segmentation and identification process can produce optimal accuracy. To get maximum results, it takes several pre-processing stages on the image to be used. To achieve this, it is necessary to perform Optical Character Recognition which can be done using Tesseract-OCR. The OCR program that was created was successfully used to scan or scan a quote text image if the document was lost or damaged, and it could save time for creating, processing and typing documents.","PeriodicalId":34350,"journal":{"name":"Journal of Applied Engineering and Technological Science","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Engineering and Technological Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37385/jaets.v4i1.905","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
引用次数: 0

Abstract

The development of technology in Indonesia is currently increasingly advanced in people's lives and cannot be avoided. The use of Artificial Intelligence in helping humans in dealing with problems is growing. Humans can take advantage of computer/smartphone media in today's technological era. One of its uses is Optical Character Recognition. This research is motivated by the problem where the running system requires development in terms of technology to detect characters in the quote text image, because the previous system still performs manual input. Optical Character Recognition has been widely used to extract characters contained in digital image media. The ability of OCR methods and techniques is very dependent on the normalization process as an initial process before entering into the next stages such as segmentation and identification. The image normalization process aims to obtain a better input image so that the segmentation and identification process can produce optimal accuracy. To get maximum results, it takes several pre-processing stages on the image to be used. To achieve this, it is necessary to perform Optical Character Recognition which can be done using Tesseract-OCR. The OCR program that was created was successfully used to scan or scan a quote text image if the document was lost or damaged, and it could save time for creating, processing and typing documents.
利用Tesseract实现OCR(光学字符识别)检测引号文本图像中的字符
印尼的科技发展目前在人们的生活中越来越先进,这是不可避免的。人工智能在帮助人类解决问题方面的应用越来越多。在当今的科技时代,人类可以利用电脑/智能手机媒体。它的用途之一是光学字符识别。由于之前的系统仍然采用人工输入的方式,目前运行的系统需要对引文文本图像中的字符检测技术进行开发,这是本研究的动机。光学字符识别已广泛应用于数字图像媒体中包含的字符提取。OCR方法和技术的能力非常依赖于规范化过程作为进入下一阶段(如分割和识别)之前的初始过程。图像归一化过程的目的是获得更好的输入图像,使分割和识别过程产生最佳的精度。为了获得最大的结果,需要对要使用的图像进行几个预处理阶段。为了实现这一点,有必要执行光学字符识别,这可以使用Tesseract-OCR来完成。所创建的OCR程序成功地用于扫描或扫描引用文本图像,如果文件丢失或损坏,它可以节省创建,处理和输入文件的时间。
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
CiteScore
1.50
自引率
0.00%
发文量
0
审稿时长
4 weeks
×
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:481959085
Book学术官方微信