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<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">sapi</journal-id><journal-title-group><journal-title xml:lang="ru">Системный анализ и прикладная информатика</journal-title><trans-title-group xml:lang="en"><trans-title>«System analysis and applied information science»</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2309-4923</issn><issn pub-type="epub">2414-0481</issn><publisher><publisher-name>Belarusian National Technical University</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.21122/2309-4923-2020-4-23-30</article-id><article-id custom-type="elpub" pub-id-type="custom">sapi-493</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>Обработка информации и принятие решений</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>Data processing and decision–making</subject></subj-group></article-categories><title-group><article-title>Алгоритм весового определения граничных пикселей</article-title><trans-title-group xml:lang="en"><trans-title>Weighted determination algoritm of boundary pixels</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Заерко</surname><given-names>Д. B.</given-names></name><name name-style="western" xml:lang="en"><surname>Zaerko</surname><given-names>D. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Заерко Денис Владимирович, аспирант кафедры информатики</p><p>Минск</p></bio><bio xml:lang="en"><p>Postgraduate student, Informatics department </p><p>Minsk</p></bio><email xlink:type="simple">zaerko1991@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Липницкий</surname><given-names>В. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Lipnitski</surname><given-names>V. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Липницкий Валерий Антонович, профессор, доктор технических наук, кафедра информатики</p><p>Минск</p><p> </p></bio><bio xml:lang="en"><p>Doctor of technical sciences, Professor, Informatics department</p><p>Minsk</p></bio><email xlink:type="simple">valipnitski@yandex.by</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Белорусский государственный университет информатики и радиоэлектроники</institution><country>Беларусь</country></aff><aff xml:lang="en"><institution>Belarusian State University of Informatics and Radioelectronics</institution><country>Belarus</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2020</year></pub-date><pub-date pub-type="epub"><day>28</day><month>01</month><year>2021</year></pub-date><volume>0</volume><issue>4</issue><fpage>23</fpage><lpage>30</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Заерко Д.B., Липницкий В.А., 2021</copyright-statement><copyright-year>2021</copyright-year><copyright-holder xml:lang="ru">Заерко Д.B., Липницкий В.А.</copyright-holder><copyright-holder xml:lang="en">Zaerko D.V., Lipnitski V.A.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" 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><self-uri xlink:href="https://sapi.bntu.by/jour/article/view/493">https://sapi.bntu.by/jour/article/view/493</self-uri><abstract/><trans-abstract xml:lang="en"><p>While working with digital noise reduction techniques, which are based on theory of convolution matrix and used convolution operation, it necessary to use algorithms to bypass boundary pixels in the image pixel matrix. The problem exists because convolution itself algorithm have peculiarity, it mean that peculiarity convolution kernel used to each element of pixel matrix. That feature characterize a lot of classes of methods which used idea of convolution matrix. There are a lot of primitive ways to solve it, but none of these ways made a consensus between economical use of resources and filling border pixels with colour coding, which is not so far from colours of corresponding pixels. The object of research is pixel matrix of image. The subject of study is algorithms for filling boundary pixels when superimposing a convolution matrix on a pixel matrix of an image. The main target is creating of effective filled algorithm for border pixels which are close to code colour to relation pixels for used in convolution matrix. Filled border pixels will use to operation convolution for each pixels original image. Algorithm of filled border pixels by step of applied convolution kernel anchors to the pixel, when pixel accessing in convolution algorithm goes beyond the pixel matrix of the original image. Algorithm takes into account the «special» cases of overstepping and allows to do fast calculation to determine the colour code of the missing pixel. The algorithm is simple to program and easily integrates with the basic convolution matrix algorithm in digital image defects.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>пиксельная матрица</kwd><kwd>дефекты цифрового изображения</kwd><kwd>подавление цифрового шума</kwd><kwd>операция двумерной свертки</kwd><kwd>шумофильтрация</kwd><kwd>граничные пиксели</kwd><kwd>полутоновые изображения</kwd></kwd-group><kwd-group xml:lang="en"><kwd>pixel matrix</kwd><kwd>digital image defects</kwd><kwd>digital noise suppression</kwd><kwd>2D convolution</kwd><kwd>noise filtering</kwd><kwd>boundary pixels</kwd><kwd>halftone image</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Гашников М. В. Методы компьютерной обработки изображений., Методы компьютерной обработки изображений / Под ред. В. А. 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