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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/564
DC FieldValueLanguage
dc.contributor.authorNguyen Phuc Vinh Phaten_US
dc.date.accessioned2020-03-12T17:04:01Z-
dc.date.available2020-03-12T17:04:01Z-
dc.date.issued2016-
dc.identifier.urihttp://epub.vgu.edu.vn/handle/dlibvgu/564-
dc.description.abstractThe advancement of computer vision technology has significantly improved various areas. One of the most useful applications of computer vision is Optical Character Recognition (OCR). One problem in an OCR system is how to extract. and recognize the characters inside the document image. This thesis proposes an approach to solving such a problem by using the k-nearest neighbor (k-NN) method, one of the simplest but most effective machine learning algorithms. This thesis also provides a simple fully-functional OCR program to calculate the accuracy and robustness of k-NN in an OCR. system. The program is implemented in Python with supporting packages such as OpenCV and scikit-learn. The result of this research yielded an average accuracy of 94% for the implemented OCR system, with acceptable building and query time.en_US
dc.language.isoenen_US
dc.publisherVietnamese-German Universityen_US
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectOptical character recognitionen_US
dc.subjectK-nearest neighbor methoden_US
dc.titleK-nearest neighbor method for optical character recognitionen_US
dc.typeThesisen_US
item.fulltextWith Fulltext-
item.languageiso639-1other-
item.grantfulltextrestricted-
Appears in Collections:Electrical Engineering and Information Technology (EEIT)
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