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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Published in:ITM web of conferences 2020, Vol.35, p.7005
Main Authors: Sidnyaev, Nikolay I., Opletina, Nadezhda V., Butenko, Yulia I., Kazanceva, Elizaveta S.
Format: Article
Language:English
Subjects:
Character recognition
Collection
Handwriting recognition
Image quality
Object recognition
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creator Sidnyaev, Nikolay I.
Opletina, Nadezhda V.
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Kazanceva, Elizaveta S.
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”.
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subjects Character recognition
Collection
Handwriting recognition
Image quality
Object recognition
title Probably-Statistical Method for Written Signs Recognition Using the Measure of Proximity
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