J. Mombach, Cristiane B. R. Ferreira, J. P. Félix, R. Salvini, Fabrízzio Soares
{"title":"Mirrored and Rotated Letters in Children Spellings: An Automatic Analysis Approach","authors":"J. Mombach, Cristiane B. R. Ferreira, J. P. Félix, R. Salvini, Fabrízzio Soares","doi":"10.1109/CCECE47787.2020.9255765","DOIUrl":null,"url":null,"abstract":"Spelling tests for children are a typical activity in primary schools and clinics specialized in child development. Commonly, some child's letters can be mirrored or rotated, and Optical Character Systems (OCRs) do not recognize nonstandard letters. Consequently, automatic evaluation approaches are harmed in this context. Furthermore, depending on the child's age, identifying mirrored or rotated letters can support earlier diagnoses of learning disabilities, such as dyslexia or dysgraphia. Therefore, we propose a method for identifying the occurrence of mirrored and rotated letters in children's spellings. The approach uses image processing techniques to extract letters from paper tests and performs transformations so it can be recognized automatically. Preliminary results indicate a promising approach, reaching an accuracy of 96% for mirrored letters recognition and 98% in rotated letters.","PeriodicalId":296506,"journal":{"name":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCECE47787.2020.9255765","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
Spelling tests for children are a typical activity in primary schools and clinics specialized in child development. Commonly, some child's letters can be mirrored or rotated, and Optical Character Systems (OCRs) do not recognize nonstandard letters. Consequently, automatic evaluation approaches are harmed in this context. Furthermore, depending on the child's age, identifying mirrored or rotated letters can support earlier diagnoses of learning disabilities, such as dyslexia or dysgraphia. Therefore, we propose a method for identifying the occurrence of mirrored and rotated letters in children's spellings. The approach uses image processing techniques to extract letters from paper tests and performs transformations so it can be recognized automatically. Preliminary results indicate a promising approach, reaching an accuracy of 96% for mirrored letters recognition and 98% in rotated letters.