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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">10.21122/2309-4923-2026-1-60-68</article-id><article-id custom-type="elpub" pub-id-type="custom">sapi-800</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>Бинаризация изображения статической подписи: предобработка и оценка качества</article-title><trans-title-group xml:lang="en"><trans-title>Binarization of a static signature image: preprocessing and its quality assessment</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.</p><p>г. Минск, 220012</p></bio><bio xml:lang="en"><p>Yuliya I. Golub – PhD, Associate Professor.</p><p>Minsk, 220012</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.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Старовойтов Валерий Васильевич – доктор технических наук, профессор. </p><p>г. Минск, 220012</p></bio><bio xml:lang="en"><p>Valery Starovoitov – Doctor of Sciences and Professor.</p><p>Minsk, 220012</p></bio><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>The 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>2026</year></pub-date><pub-date pub-type="epub"><day>10</day><month>04</month><year>2026</year></pub-date><volume>0</volume><issue>1</issue><fpage>60</fpage><lpage>68</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Голуб Ю.И., Старовойтов В.В., 2026</copyright-statement><copyright-year>2026</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.</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/800">https://sapi.bntu.by/jour/article/view/800</self-uri><abstract><p>В статье мы представляем сравнительное исследование методов бинаризации цветных изображений статических подписей, выполненных шариковыми ручками разных типов и цветов. Бинаризация представления подписи – это первый шаг перед вычислением ее признаков и анализом подлинности. Из-за неравномерности нанесения на бумагу пасты особую сложность представляют изображения подписей, выполненных шариковыми ручками. Выполнено сравнение методов предобработки цифровых изображений подписей, направленных на сохранение формы линий на их бинарном представлении. Сравнительный анализ методов бинаризации цветных изображений подписи выполнен на примере четырех методов, относящихся к разным классам: с глобальным порогом (Отсу, Капура), с локально-адаптивным порогом (Саувола) и метод прямого индексирования цветового пространства RGB на белые и черные пиксели. Впервые предложены эмпирические объективные критерии качества бинарного представления подписи в отсутствие ее эталона, основанные на анализе связных компонент и скелета бинарного представления подписи. Эксперименты выполнялись на изображениях из общедоступной базы CEDAR и базе подписей, собранных в процессе исследований. Показано, что метод Капура обеспечивает наилучшее сохранение формы подписи на ее бинарном представлении, превосходя остальные методы, включая популярный метод Отсу. Формирование бинарного представления подписи предлагается выполнять в четыре этапа: сканирование подписи в цвете (модель RGB) с разрешением 300 или 600 DPI, преобразование цветного изображения в полутоновое методом PCA, бинаризацию методом Капура, постобработку бинарного изображения. Данная методика формирования бинарного изображения подписи ориентирована на разработку систем верификации статических подписей.</p></abstract><trans-abstract xml:lang="en"><p>In the paper we present a comparative study of binarization methods for color images of static signatures made with ballpoint pens of different types and colors. Signature image binarization is the first step before calculating its features and verification. Because of the uneven flow of ink from ballpoint pens, images of signatures made with such pens present particular challenges. A comparison of digital signature image preprocessing methods aimed at preserving the shape of the signature lines in the binary representations is conducted. A comparative analysis of binarization methods for color signature images is performed based on four methods from different classes: global thresholding (Otsu, Kapura), locally adaptive thresholding (Sauvola), and a method of direct indexing the RGB color space into two classes: white and black pixels. For the first time, empirical objective criteria for the quality of a binary signature representation in the absence of a reference are proposed, based on the analysis of connected components and the skeleton of the binary signature representation. Experiments were performed on images from the publicly available CEDAR database and a database of signatures collected during the research. It has been shown that Kapur's method provides the best preservation of signature form in its binary representation, outperforming other methods, including the popular Otsu method. We propose a four-step procedure for generating a binary signature representation. This procedure consists of scanning a color signature at 300 or 600 DPI in the RGB model, converting the color image to grayscale using principal component analysis (PCA), binarization by the Kapoor method, and post-processing the binary image. This method is intended for developing static signature verification systems.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>статическая подпись</kwd><kwd>обработка изображений</kwd><kwd>бинаризация</kwd><kwd>связные компоненты</kwd><kwd>скелетизация</kwd><kwd>оценка качества изображения в отсутствие эталона</kwd></kwd-group><kwd-group xml:lang="en"><kwd>static signature</kwd><kwd>image processing</kwd><kwd>binarization</kwd><kwd>connected components</kwd><kwd>skeletonization</kwd><kwd>no-reference image quality assessment</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">Singla, A. Exploring offline signature verification techniques: A survey based on methods and future directions / A. Singla, A. Mittal // Multimedia Tools and Applications. 2024. Vol. 84, № 6. P. 2835–2875. 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