Erik Miguel de Elias, P. M. Tasinaffo, Roberto Hirata Junior
{"title":"Alignment, Scale and Skew Correction for Optical Mark Recognition Documents Based","authors":"Erik Miguel de Elias, P. M. Tasinaffo, Roberto Hirata Junior","doi":"10.1109/WVC.2019.8876933","DOIUrl":null,"url":null,"abstract":"Acquiring an OMR (Optical Mark Recognition) reading equipment can be impracticable to some companies or individuals due to its costs. Computational software solutions can be more attractive, but they require specific page format or page layout, such as specific marks to be used when recognizing any OMR document. In this paper, we propose a way to treat skew, translation, scale and alignment using a base document as reference due to the intrinsic characteristics of the problem. Key points are found by a pattern matching algorithm and used for the document image transformation. The method does not require specific layout, needing less formatting, allowing non-experts to create the form using ordinary software and scanners. Two experiments were executed: one with 40 images distorted randomly from a document clipping, and the second one with 1034 images of real student tests. Both experiments reached high overall accuracy.","PeriodicalId":144641,"journal":{"name":"2019 XV Workshop de Visão Computacional (WVC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 XV Workshop de Visão Computacional (WVC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WVC.2019.8876933","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
Acquiring an OMR (Optical Mark Recognition) reading equipment can be impracticable to some companies or individuals due to its costs. Computational software solutions can be more attractive, but they require specific page format or page layout, such as specific marks to be used when recognizing any OMR document. In this paper, we propose a way to treat skew, translation, scale and alignment using a base document as reference due to the intrinsic characteristics of the problem. Key points are found by a pattern matching algorithm and used for the document image transformation. The method does not require specific layout, needing less formatting, allowing non-experts to create the form using ordinary software and scanners. Two experiments were executed: one with 40 images distorted randomly from a document clipping, and the second one with 1034 images of real student tests. Both experiments reached high overall accuracy.