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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">10.21122/2309-4923-2024-1-4-11</article-id><article-id custom-type="elpub" pub-id-type="custom">sapi-653</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>Системный анализ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>System analysis</subject></subj-group></article-categories><title-group><article-title>Оценка качества цифровых изображений изломов металлических объектов.</article-title><trans-title-group xml:lang="en"><trans-title>Image  quality  assessment  of  fractures  of  metallic objects</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>Голуб</surname><given-names>Ю. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Golub</surname><given-names>Yu. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Голуб Юлия Игоревна, кандидат технических наук, доцент, старший научный сотрудник</p><p>Минск</p></bio><bio xml:lang="en"><p>Yuliya I. Golub, PhD, Associate Professor, Senior Research Fellow</p><p>Minsk</p></bio><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Старовойтов</surname><given-names>В. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Starovoitov</surname><given-names>V. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Старовойтов Валерий Васильевич, доктор технических наук, профессор, главный научный сотрудник</p><p>Минск</p></bio><bio xml:lang="en"><p>Starovoitov Valery, Doctor of Sciences and professor of computer science. He is a Principal research fellow</p><p>Minsk</p></bio><email xlink:type="simple">valerys@newman.bas-net.by</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Объединенный институт проблем информатики Национальной академии наук Беларуси</institution><country>Беларусь</country></aff><aff xml:lang="en"><institution>United institute of informatics problems of the National Academy of Sciences of Belarus</institution><country>Belarus</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2024</year></pub-date><pub-date pub-type="epub"><day>08</day><month>05</month><year>2024</year></pub-date><volume>0</volume><issue>1</issue><fpage>4</fpage><lpage>11</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Голуб Ю.И., Старовойтов В.В., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Голуб Ю.И., Старовойтов В.В.</copyright-holder><copyright-holder xml:lang="en">Golub Y.I., Starovoitov V.V.</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/653">https://sapi.bntu.by/jour/article/view/653</self-uri><abstract><p>Рассматривается задача вычисления количественной оценки качества цифровых изображений изломов металлических объектов, зарегистрированных фотоаппаратом и цифровым микроскопом. Оценка качества выполняется в отсутствии эталонных изображений. В статье представлен подход, в основе которого лежит вычисление локальных оценок с последующим анализом их распределения. Исследованы разные варианты оценочных функций для резкости, яркости и контраста, описанные в отечественной и зарубежной литературе. Отобраны те из них, распределение которых унимодально. Показано, что среднее локальных оценок является приемлемой обобщающей характеристикой качества изображения, если они имеют нормальное (гауссово) распределение. В этом случае среднее является одним из его параметров. В ином случае более точными количественными характеристиками качества изображения могут служить параметры распределения Вейбулла. Предложенный подход позволяет более объективно делить множество изображений анализируемых объектов на две группы – имеющие удовлетворительное или неудовлетворительное качество для выполнения экспертных исследований по изображениям.</p></abstract><trans-abstract xml:lang="en"><p>The problem of calculating a quantitative quality assessment of digital images of metal object fractures recorded by a camera or a digital microscope is considered. Quality assessment is performed when the reference images are absent. The paper presents an approach based on calculation of local estimates followed by analysis of their distribution. Several variants for calculation of local estimates have been studied. Those whose distribution is unimodal were selected. It is shown that the average of local estimates is an acceptable general characteristic of image quality if they have a normal (Gaussian) distribution. In this case, the average is one of its parameters. Otherwise, the parameters of the Weibull distribution can serve as more accurate quantitative characteristics of image quality in general. The proposed approach divides more objectively the set of the analyzed images into two groups those with satisfactory or unsatisfactory quality for performing expert studies using images. Examples of the quality assessment of different object images recorded at different resolutions are presented.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>цифровое изображение</kwd><kwd>количественная оценка качества изображения</kwd><kwd>излом металла</kwd><kwd>распределение Вейбулла</kwd><kwd>нормальное распределение</kwd></kwd-group><kwd-group xml:lang="en"><kwd>digital image</kwd><kwd>quantitative assessment of image quality</kwd><kwd>metal fracture</kwd><kwd>Weibull distribution</kwd><kwd>normal distribution</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">Голуб, Ю.И., Старовойтов В.В. Оценка качества цифровых изображений. – Минск: ОИПИ НАН Беларуси, 2023. – 252 с.</mixed-citation><mixed-citation xml:lang="en">Golub, Y.I., Starovoitov, V.V. 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