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Presentation of an effective method of text recognition in the image, based on the criteria of similarity of structural models of symbols similarity criteria

Presentation of an effective method of text recognition in the image, based on the criteria of similarity of structural models of symbols similarity criteria

Abstract

The object of research is the methods of handwriting recognition. The article reviews the basic principles of optical recognition. The aim of the work is to present an algorithm for text recognition in the image, which has high accuracy with a small training sample. To achieve this goal, an original similarity criterion is proposed, which can be used to effectively compare the formed structural models of symbols. The reader is offered a detailed consideration of the algorithm of the mentioned similarity criterion. Ref. 5, pic. 4

Об’єктом дослідження є методи розпізнавання рукописних символів. У статті зроблено огляд основних принципів оптичного розпізнавання. Метою роботи є представлення алгоритму розпізнавання тексту на зображенні, що має високу точність при невеликій навчаючій вибірці. Для досягнення мети пропонується оригінальний критерій схожості, який можна використати для ефективного порівняння сформованих структурних моделей символів. До уваги читача пропонується детальний розгляд алгоритму згаданого критерія схожості. Бібл. 5, іл. 4

Keywords

structural model, розпізнавання символів, character recognition, bipartite graph, структурна модель, дводольний граф, similarity criterion, критерій схожості

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold