Probably-Statistical Method for Written Signs Recognition Using the Measure of Proximity
The paper describes ways to recognize written signs when the nature of the source is absolutely unclear and the seemingly obvious possibilities for solving the problem are not clear as well. The article deals with methods of recognition of binary images in order to compare them and highlight the bes...
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EDP Sciences
2020-01-01
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Series: | ITM Web of Conferences |
Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2020/05/itmconf_itee2020_07005.pdf |
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doaj-6505f3361c434ee794426caf9274abec2021-05-28T14:51:51ZengEDP SciencesITM Web of Conferences2271-20972020-01-01350700510.1051/itmconf/20203507005itmconf_itee2020_07005Probably-Statistical Method for Written Signs Recognition Using the Measure of ProximitySidnyaev Nikolay I.0Opletina Nadezhda V.1Butenko Yulia I.2Kazanceva Elizaveta S.3Bauman Moscow State Technical UniversityBauman Moscow State Technical UniversityBauman Moscow State Technical UniversityBauman Moscow State Technical UniversityThe paper describes ways to recognize written signs when the nature of the source is absolutely unclear and the seemingly obvious possibilities for solving the problem are not clear as well. The article deals with methods of recognition of binary images in order to compare them and highlight the best. The images of documents are obtained with the help of a camera. The quality is low. The images of the collection were segmented and passed binaryization. A control sample was selected to test the recognition methods from the resulting collection. The paper describes the method of comparing images, their advantages and disadvantages when recognizing handwritten shorthand characters. The results obtained by comparing the characters of the control sample allowed determining the best method “method of comparison of forms”.https://www.itm-conferences.org/articles/itmconf/pdf/2020/05/itmconf_itee2020_07005.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sidnyaev Nikolay I. Opletina Nadezhda V. Butenko Yulia I. Kazanceva Elizaveta S. |
spellingShingle |
Sidnyaev Nikolay I. Opletina Nadezhda V. Butenko Yulia I. Kazanceva Elizaveta S. Probably-Statistical Method for Written Signs Recognition Using the Measure of Proximity ITM Web of Conferences |
author_facet |
Sidnyaev Nikolay I. Opletina Nadezhda V. Butenko Yulia I. Kazanceva Elizaveta S. |
author_sort |
Sidnyaev Nikolay I. |
title |
Probably-Statistical Method for Written Signs Recognition Using the Measure of Proximity |
title_short |
Probably-Statistical Method for Written Signs Recognition Using the Measure of Proximity |
title_full |
Probably-Statistical Method for Written Signs Recognition Using the Measure of Proximity |
title_fullStr |
Probably-Statistical Method for Written Signs Recognition Using the Measure of Proximity |
title_full_unstemmed |
Probably-Statistical Method for Written Signs Recognition Using the Measure of Proximity |
title_sort |
probably-statistical method for written signs recognition using the measure of proximity |
publisher |
EDP Sciences |
series |
ITM Web of Conferences |
issn |
2271-2097 |
publishDate |
2020-01-01 |
description |
The paper describes ways to recognize written signs when the nature of the source is absolutely unclear and the seemingly obvious possibilities for solving the problem are not clear as well. The article deals with methods of recognition of binary images in order to compare them and highlight the best. The images of documents are obtained with the help of a camera. The quality is low. The images of the collection were segmented and passed binaryization. A control sample was selected to test the recognition methods from the resulting collection. The paper describes the method of comparing images, their advantages and disadvantages when recognizing handwritten shorthand characters. The results obtained by comparing the characters of the control sample allowed determining the best method “method of comparison of forms”. |
url |
https://www.itm-conferences.org/articles/itmconf/pdf/2020/05/itmconf_itee2020_07005.pdf |
work_keys_str_mv |
AT sidnyaevnikolayi probablystatisticalmethodforwrittensignsrecognitionusingthemeasureofproximity AT opletinanadezhdav probablystatisticalmethodforwrittensignsrecognitionusingthemeasureofproximity AT butenkoyuliai probablystatisticalmethodforwrittensignsrecognitionusingthemeasureofproximity AT kazancevaelizavetas probablystatisticalmethodforwrittensignsrecognitionusingthemeasureofproximity |
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1721423244803702784 |