Document Image Binarization Process

Marcel Prodan, C. Boiangiu
{"title":"Document Image Binarization Process","authors":"Marcel Prodan, C. Boiangiu","doi":"10.18662/brain/14.2/446","DOIUrl":null,"url":null,"abstract":"Technology has made significant strides in recent years, which accounts for how pervasive it is in our daily lives. In order to address the fundamental issue with historical document preservation, namely their degeneration, this work suggests using new technology. The method is built on pieces of artificial intelligence that can read the writing from a page and recognize the useful information, converting it into a digital version. Contrary to photographing or scanning, binarizing a document is a considerably more effective method, both in terms of quality—the legibility of the writing—and quantity—the amount of memory needed to retain the resulting image. According to common assessment measures, the suggested fully convolutional network manages to deliver results that are comparable to those of other solutions of a similar nature.","PeriodicalId":44081,"journal":{"name":"BRAIN-Broad Research in Artificial Intelligence and Neuroscience","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"BRAIN-Broad Research in Artificial Intelligence and Neuroscience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18662/brain/14.2/446","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"NEUROSCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Technology has made significant strides in recent years, which accounts for how pervasive it is in our daily lives. In order to address the fundamental issue with historical document preservation, namely their degeneration, this work suggests using new technology. The method is built on pieces of artificial intelligence that can read the writing from a page and recognize the useful information, converting it into a digital version. Contrary to photographing or scanning, binarizing a document is a considerably more effective method, both in terms of quality—the legibility of the writing—and quantity—the amount of memory needed to retain the resulting image. According to common assessment measures, the suggested fully convolutional network manages to deliver results that are comparable to those of other solutions of a similar nature.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
文档图像二值化过程
近年来,科技取得了巨大的进步,这说明了它在我们的日常生活中是多么普遍。为了解决历史文献保存的根本问题,即历史文献的退化,本工作建议使用新技术。该方法建立在人工智能的基础上,人工智能可以读取页面上的文字,识别有用的信息,并将其转换为数字版本。与拍照或扫描相反,对文档进行二值化是一种有效得多的方法,无论是从质量(文字的易读性)还是从数量(保留生成图像所需的内存量)两方面来说都是如此。根据常见的评估措施,建议的全卷积网络设法提供与其他类似性质的解决方案相当的结果。
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 去求助
来源期刊
自引率
47.80%
发文量
0
审稿时长
2 weeks
期刊最新文献
Psychological Complications During Military Operations in Ukraine: Neurobiological Effects Results of the Implementation of a Comprehensive Socio-Psychological Program to Foster Professional Empathy Among Professionals in the Helping Professions Can Neural Networks Enhance Physics Simulations? National Strategy of Information Society in the Realities of Ukraine Document Image Binarization Process
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1