R. Lins, R. Bernardino, D. Jesus, José Mário Oliveira
{"title":"Binarizing Document Images Acquired with Portable Cameras","authors":"R. Lins, R. Bernardino, D. Jesus, José Mário Oliveira","doi":"10.1109/ICDAR.2017.348","DOIUrl":null,"url":null,"abstract":"Although made for \"family photos\" portable digital cameras, either in standalone models or embedded in cell phones, are often used to take photos of documents today. In general, such photos are sent via networks and either visualized in desktops, printed, or even transcribed via OCR. Binarization may play an important role in such a scheme. This paper follows the idea that \"no binarization algorithm is good for all kinds of images\". Non-uniform illumination, the possible interference of light sources from the environment, and non-uniform resolution are some of the problems found in photographed document images that are not present in their scanned counterparts. This paper presents a new methodology to assess binarization algorithms in different devices, taking into account the difficulties listed and the particularities of the cameras and documents.","PeriodicalId":433676,"journal":{"name":"2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 14th IAPR International Conference on Document Analysis and Recognition (ICDAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.2017.348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
Although made for "family photos" portable digital cameras, either in standalone models or embedded in cell phones, are often used to take photos of documents today. In general, such photos are sent via networks and either visualized in desktops, printed, or even transcribed via OCR. Binarization may play an important role in such a scheme. This paper follows the idea that "no binarization algorithm is good for all kinds of images". Non-uniform illumination, the possible interference of light sources from the environment, and non-uniform resolution are some of the problems found in photographed document images that are not present in their scanned counterparts. This paper presents a new methodology to assess binarization algorithms in different devices, taking into account the difficulties listed and the particularities of the cameras and documents.