R. Lins, Gabriel de F. Pe Silva, Gustavo P. Chaves, Ricardo da Silva Barboza, R. Bernardino, S. Simske
{"title":"Quality, Space and Time Competition on Binarizing Photographed Document Images","authors":"R. Lins, Gabriel de F. Pe Silva, Gustavo P. Chaves, Ricardo da Silva Barboza, R. Bernardino, S. Simske","doi":"10.1145/3573128.3604903","DOIUrl":null,"url":null,"abstract":"Document image binarization is a fundamental step in many document processes. No binarization algorithm performs well on all types of document images, as the different kinds of digitalization devices and the physical noises present in the document and acquired in the digitalization process alter their performance. Besides that, the processing time is also an important factor that may restrict its applicability. This competition on binarizing photographed documents assessed the quality, time, space, and performance of five new algorithms and sixty-four \"classical\" and alternative algorithms. The evaluation dataset is composed of laser and deskjet printed documents, photographed using six widely-used mobile devices with the strobe flash on and off, under two different angles and places of capture.","PeriodicalId":310776,"journal":{"name":"Proceedings of the ACM Symposium on Document Engineering 2023","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ACM Symposium on Document Engineering 2023","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3573128.3604903","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Document image binarization is a fundamental step in many document processes. No binarization algorithm performs well on all types of document images, as the different kinds of digitalization devices and the physical noises present in the document and acquired in the digitalization process alter their performance. Besides that, the processing time is also an important factor that may restrict its applicability. This competition on binarizing photographed documents assessed the quality, time, space, and performance of five new algorithms and sixty-four "classical" and alternative algorithms. The evaluation dataset is composed of laser and deskjet printed documents, photographed using six widely-used mobile devices with the strobe flash on and off, under two different angles and places of capture.