sudexpertТеория и практика судебной экспертизыTheory and Practice of Forensic Science1819-27852587-7275The Russian Federal Centre of Forensic Science10.30764/1819-2785-2020-4-90-97sudexpert-626Research ArticleДИСКУССИИDISCUSSIONSОценка качества и идентификация отпечатков пальцев путем анализа структурных свойств изображенияQuality Assessment and Identification of Fingerprints by Analysis of the Image’s Structural PropertiesАсатрянД. Г.AsatryanD. G.

Асатрян Давид Гегамович – д. т. н., ведущий научный сотрудник Института проблем информатики и автоматизации Национальной Академии Наук Армении, руководитель научно-исследовательского центра критических технологий Российско-Армянского университета

Ереван 0014

Ереван 0052

Asatryan David Geghamovich – Doctor of Engineering, Leading Scientist of the Institute for Informatics and Automation Problems of National Academy of Sciences of Armenia, Head of the Research Center for Critical Technologies of Russian-Armenian University

Yerevan 0014

Yerevan 0052

dasat@ipia.sci.amИнститут проблем информатики и автоматизации НАН РА; Российско-Армянский университетАрменияInstitute for Informatics and Automation Problems of National Academy of Sciences of Armenia; Russian-Armenian UniversityArmenia2020271220201549097Copyright © Асатрян Д.Г., 20202020Асатрян Д.Г.Asatryan D.G.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.tipse.ru/jour/article/view/626

Рассмотрена задача оценки качества изображения отпечатков пальцев с применением пространственных методов анализа. Предложено использовать математическую модель, разработанную ранее для описания совокупности магнитуд градиента изображения. Модель основана на двухпараметрическом распределении Вейбулла. Для оценки качества отпечатков пальцев предложены два подхода. Первый реализуется с помощью так называемого метода сравнения с эталоном (Full Reference), когда сравниваются значения статистических оценок параметров распределения Вейбулла. Приведены результаты решения задачи идентификации потовых пор этим методом. Второй подход называется «безэталонным» (No-Reference) и применяется для оценки качества отпечатков при анализе и выделении информативности их отдельных участков. В качестве характеристики качества предлагается использовать карту размытости изображения, а в качестве меры размытости – статистическую оценку параметра формы распределения Вейбулла. Параметр формы оценивается в каждой точке изображения по совокупности магнитуд градиента изображения в окрестности точки, при этом применяется разработанная ранее методика построения карты размытости. Эффективность предложенных подходов иллюстрируется конкретными примерами.

The paper addresses the problem of assessing the quality of fingerprint images using spatial analysis methods. The author proposes using the previously developed mathematical model to describe the set of magnitudes of the image gradient. The model is based on the two-parameter Weibull distribution. The author proposes two approaches to assess the quality of fingerprints. The first approach is implemented by the so-called “Full reference method”, which compares the Weibull distribution parameters’ values of statistical estimates. The results of identifying sweat pores using this method are presented. The second approach is called the “No-Reference method” and is used to assess fingerprints’ quality when analyzing and identifying the information content of their individual sections. It is proposed to use an image blur map as a quality characteristic and a statistical estimate of the Weibull distribution shape parameter as a measure of the blur. The shape parameter is estimated at each image point by the combination of magnitudes of the image gradient in the vicinity of the point; in this, the previously developed blur mapping technique is applied. The specific examples illustrate effectiveness of the proposed approaches.

отпечаток пальцакачество изображенияэталонный методбезэталонный методразмытиекарта качествапотовые порыраспределение Вейбуллаfingerprintimage qualityfull reference methodno-reference methodblurquality mapsweat poresWeibull distributionReferencesOlsen M.A., Šmida V., Busch C. Finger Image Quality Assessment Features – Definitions and Evaluation // IET Biometrics. 2016. Vol. 5. No. 2. P. 47–64. https://doi.org/10.1049/iet-bmt.2014.0055Olsen M.A., Šmida V., Busch C. Finger Image Quality Assessment Features – Definitions and Evaluation. IET Biometrics. 2016. Vol. 5. No. 2. P. 47–64. https://doi.org/10.1049/iet-bmt.2014.0055Yao Zh., Le Bars J., Charrier C., Rosenberger C. Literature Review of Fingerprint Quality Assessment and Its Evaluation // IET Biometrics. 2016. Vol. 5. No. 3. P. 243–251. https://doi.org/10.1049/iet-bmt.2015.0027Yao Zh., Le Bars J., Charrier C., Rosenberger C. Literature Review of Fingerprint Quality Assessment and Its Evaluation. IET Biometrics. 2016. Vol. 5. No. 3. 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The authors declare that there are no conflicts of interest present.