<?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE book PUBLIC "-//NLM//DTD BITS Book Interchange DTD v2.3 20210610//EN" "BITS-book2.3.dtd"> <book xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" book-type="conference-thesis" dtd-version="2.3" xml:lang="en"> <front> <book-meta>    <title-group>  <book-title xml:lang="en">Педагогические инновации: от теории к практике</book-title>   <trans-title-group xml:lang="ru"> <trans-title>Педагогические инновации: от теории к практике</trans-title> </trans-title-group>  </title-group>     <event>  <event-desc xml:lang="ru">Педагогические инновации: от теории к практике</event-desc>   <event-desc xml:lang="en">Pedagogical innovations: from theory to practice</event-desc>   <conf-date> <day>01</day> <month>01</month> <year>1900</year> </conf-date>    <conf-loc xml:lang="en">Чебоксары</conf-loc>  </event>   <publisher> <publisher-name>Центр научного сотрудничества «Интерактив плюс»</publisher-name> </publisher>    <pub-date pub-type="collection"> <year>1900</year> </pub-date>    <permissions> <copyright-statement>Copyright &#x00A9; Veronika Malsagova, Tatiana L. Fomicheva, 1900</copyright-statement> <copyright-year>1900</copyright-year> <license license-type="open-access" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"> <license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p> </license> </permissions>  </book-meta> <book-part book-part-type="abstract"> <book-part-meta>   <book-id custom-type="publisher-id" pub-id-type="custom">508752</book-id> <title-group>  <chapter-title xml:lang="en">Text recognizing. Machine vision</chapter-title>   <trans-title-group xml:lang="ru"> <trans-title>Распознавание текста. Системы машинного зрения</trans-title> </trans-title-group>  </title-group>  <contrib-group>   <contrib contrib-type="author" id="author1">   <name-alternatives>  <name name-style="eastern" xml:lang="ru"> <surname>Мальсагова</surname> <given-names>Вероника</given-names> </name>   <name name-style="western" xml:lang="en"> <surname>Malsagova</surname> <given-names>Veronika</given-names> </name>   </name-alternatives>  <email xlink:type="simple">veronika2001shumkova@gmail.com</email> <xref ref-type="aff" rid="aff1"/> </contrib>   <contrib contrib-type="author" id="author2">   <name-alternatives>  <name name-style="eastern" xml:lang="ru"> <surname>Фомичева</surname> <given-names>Татьяна Леонидовна</given-names> </name>   <name name-style="western" xml:lang="en"> <surname>Fomicheva</surname> <given-names>Tatiana Leonidovna</given-names> </name>   </name-alternatives>  <email xlink:type="simple">tatlfom@mail.ru</email> <xref ref-type="aff" rid="aff1"/> </contrib>   <aff-alternatives id="aff1">   <aff xml:lang="ru">  <institution>ФГОБУ ВО «Финансовый университет при Правительстве Российской Федерации»</institution>   <country>Россия</country> </aff>    <aff xml:lang="en">  <institution>FSFEI of HE &quot;Financial University under the Government of the Russian Federation&quot;</institution>   <country>Russia</country> </aff>   </aff-alternatives>  </contrib-group>       <abstract xml:lang="en"> <p>the article provides an overview of the library machine vision for optical character recognition (OCR) in the image. Machine vision methods are used in various fields: from medical imaging to remote sensing, industrial control, document processing, nanotechnology and multimedia databases. Optical character recognition is part of the solution of the most important applied problems (document recovery, recognition of car numbers, publication of text on a web page, digitization of books, etc.), which is an investigated problem in the fields of machine and computer vision) [4].</p> </abstract>    <trans-abstract xml:lang="ru"> <p>в статье представлен обзор систем машинного зрения для оптического распознавания символов (OCR-optical character recognition) в изображении. Методы машинного зрения применяются в различных областях: от медицинской визуализации до дистанционного зондирования, регулирования производственных процессов, обработки документов, нанотехнологий и мультимедийных баз данных. Оптическое распознавание символов является частью решения важнейших прикладных задач (восстановление документов, распознавание номеров автомобилей, публикация текста на веб-странице, оцифровка книг и др.), и является исследуемой проблемой в области машинного и компьютерного зрения) [4].</p> </trans-abstract>         <kwd-group xml:lang="ru">  <kwd>распознавание</kwd>  <kwd>машинное зрение</kwd>  <kwd>Тессеракт</kwd>  <kwd>Окропус</kwd>  </kwd-group>    <kwd-group xml:lang="en">  <kwd>recognition</kwd>  <kwd>machine vision</kwd>  <kwd>Tesseract</kwd>  <kwd>OCRopus</kwd>  </kwd-group>      </book-part-meta> </book-part> </front>  <back> <ref-list> <title>References</title>  <ref id="ref1"> <label>1</label> <citation-alternatives>   <mixed-citation xml:lang="en">Davies E.R. Computer and Machine Vision: Theory, Algorithms, Practicalities (4th ed.) / Academic Press. – P. 410–411. 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