sapiСистемный анализ и прикладная информатика«System analysis and applied information science»2309-49232414-0481Belarusian National Technical University10.21122/2309-4923-2024-4-54-52sapi-707Research ArticleОбработка информации и принятие решенийData processing and decision–makingБезэталонная оценка качества цифрового изображения статической подписиNo-reference digital image quality assessment of offline signatureГолубЮ. И.GolubY. I.

Голуб Юлия Игоревна, кандидат технических наук, доцент, ведущий научный сотрудник Минск

Yuliya I. Golub, PhD, Associate Professor, Leading Researcher Minsk

Объединенный институт проблем информатики НАН БеларусиБеларусьUnited institute of informatics problems of the National Academy of Sciences of BelarusBelarus202430122024045462Copyright © Голуб Ю.И., 20242024Голуб Ю.И.Golub Y.I.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://sapi.bntu.by/jour/article/view/707

Цель данной работы заключается в разработке простого критерия оценки качества цифрового изображения подписи, которая была выполнена на бумаге и отсканирована (т.е. статическая подпись). Предложенный подход может быть использован как инструмент мониторинга образцов подписи в биометрических системах распознавания для контроля качества данных. Например, при регистрации изображения, выборе метода обработки и настройки его параметров, после выполнения различных операций (поворота, масштабирования) и необходимости оценки и анализа полученных изображений подписи. Также в работе описаны факторы, которые могут негативно влиять на качество статической подписи, и выполнен экспериментальный анализ на цифровых изображениях подписей, представленных в базах CEDAR, BHSig260-Bengali, SigComp2009 и изображениях, собранных в процессе выполнения исследования.

The purpose of this paper is to develop a simple criterion for image quality assessment of a signature scanned from a paper (i. e., a static or offline signature). A new approach to no-reference assessment of the quality of a binary signature image is proposed, which can be useful as a tool for monitoring signature samples in biometric recognition systems to control data quality. For example, it can be used during image registration, selection of processing methods and its parameters adjustment, after performing various operations (such as rotation or scaling) and the need to evaluate and analyze the obtained signature images. The paper also describes factors that can negatively affect the quality of a static signature. The experimental analysis was performed on digital images of signatures available in the CEDAR, BHSig260-Bengali, SigComp2009 databases and images collected during the research.

биометрическая системабинарное изображениецифровое изображение подписи человекаоценка качества бинарных изображенийрукописная подписьbiometric systembinary imagedigital image of human signatureimage quality assessment of binary imagehandwriting signatureReferencesFernandez F.A. Biometric sample quality and its application to multimodal authentication systems. Universidad Politecnica de Madrid. Madrid, Spain. 2008 . 50 p.Fernandez F.A. Biometric sample quality and its application to multimodal authentication systems. Universidad Politecnica de Madrid. Madrid, Spain. 2008 . 50 p.Fairhurst M. Signature verification revisited: promoting practical exploitation of biometric technology. Electronics and Communication Engineering Journal. 1997. Vol. 9. Pр. 273-280.Fairhurst M. Signature verification revisited: promoting practical exploitation of biometric technology. Electronics and Communication Engineering Journal. 1997. Vol. 9. Pр. 273-280.Jain A., Ross A., Prabhakar S. An introduction to biometric recognition // IEEE Transactions on Circuits and Systems for Video Technology. 2004. Vol. 14. № 1. Pр. 4-20.Jain A., Ross A., Prabhakar S. An introduction to biometric recognition // IEEE Transactions on Circuits and Systems for Video Technology. 2004. Vol. 14. № 1. Pр. 4-20.Plamondon R., Srihari S.N. On-line and off-line handwriting recognition: a comprehensive survey. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2020. Vol. 22. № 1. Pр. 63–84. DOI: 10.1109/34.824821Plamondon R., Srihari S.N. On-line and off-line handwriting recognition: a comprehensive survey. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2020. Vol. 22. № 1. Pр. 63–84. DOI: 10.1109/34.824821Yogesh G., Patil A. Offline and online signature verification systems: A survey. International Journal of Research in Engineering and Technology. 2014. Vol. 3. № 3. Pр. 328-332.Yogesh G., Patil A. Offline and online signature verification systems: A survey. International Journal of Research in Engineering and Technology. 2014. Vol. 3. № 3. Pр. 328-332.Alonso-Fernandez F., Fierrez J., Ortega-Garcia J. Quality measures in biometric systems. IEEE Security & Privacy Magazine. 2011. Vol. 9. № 4. Pр. 34-41. DOI: 10.1109/msp.2011.178Alonso-Fernandez F., Fierrez J., Ortega-Garcia J. Quality measures in biometric systems. IEEE Security & Privacy Magazine. 2011. Vol. 9. № 4. Pр. 34-41. DOI: 10.1109/msp.2011.178Hameed M.M. et al. Off Sig-Sin GAN: A Deep Learning-Based Image Augmentation Model for Offline Signature Verification. Computers, Materials & Continua. 2023. Vol. 76. № 1. Pр. 1-15.Hameed M.M. et al. Off Sig-Sin GAN: A Deep Learning-Based Image Augmentation Model for Offline Signature Verification. Computers, Materials & Continua. 2023. Vol. 76. № 1. Pр. 1-15.Hafemann L.G., Sabourin R., Oliveira L.S. Offline handwritten signature verification – Literature review. 2017 seventh international conference on image processing theory, tools and applications (IPTA). IEEE. 2017. Pр. 1-8.Hafemann L.G., Sabourin R., Oliveira L.S. Offline handwritten signature verification – Literature review. 2017 seventh international conference on image processing theory, tools and applications (IPTA). IEEE. 2017. Pр. 1-8.Jain A., Flynn P., Ross A. (eds.) Handbook of biometrics. Springer, 2008. 694 p.Jain A., Flynn P., Ross A. (eds.) Handbook of biometrics. Springer, 2008. 694 p.Bouridane A., Shafique M. Signature verification and recognition: A review. In Handbook of research on image and video processing. 2008. Pр. 531-558.Bouridane A., Shafique M. Signature verification and recognition: A review. In Handbook of research on image and video processing. 2008. Pр. 531-558.Alonso-Fernandez F., Fierrez J., Ortega-Garcia J. Quality Measures in Biometric System. IEEE Security & Privacy. 2012. Vol. 10. № 6. Pр. 52-62. DOI: 10.1109/MSP.2011.178Alonso-Fernandez F., Fierrez J., Ortega-Garcia J. Quality Measures in Biometric System. IEEE Security & Privacy. 2012. Vol. 10. № 6. Pр. 52-62. DOI: 10.1109/MSP.2011.178Benini S. Biometric sample quality standards: Applications, status, and direction. Proc. NIST Biometric Quality Workshop. Gaithersburg, MD, USA, November 7-8, 2007.Benini S. Biometric sample quality standards: Applications, status, and direction. Proc. NIST Biometric Quality Workshop. Gaithersburg, MD, USA, November 7-8, 2007.Kalera M.K., Srihari S., Xu A. Offline signature verification and identification using distance statistics. International Journal of Pattern Recognition and Artificial Intelligence. 2004. Vol. 18. Pр. 1339-1360.Kalera M.K., Srihari S., Xu A. Offline signature verification and identification using distance statistics. International Journal of Pattern Recognition and Artificial Intelligence. 2004. Vol. 18. Pр. 1339-1360.Pal S. et al. Performance of an off-line signature verification method based on texture features on a large indic-script signature dataset. 2016 12th IAPR Workshop on Document Analysis Systems (DAS). IEEE. 2016. Pр. 72-77.Pal S. et al. Performance of an off-line signature verification method based on texture features on a large indic-script signature dataset. 2016 12th IAPR Workshop on Document Analysis Systems (DAS). IEEE. 2016. Pр. 72-77.Blankers V.L., van den Heuvel C.E., Franke K.Y., Vuurpijl L.G. Icdar 2009 signature verification competition. In: Proceedings of the International Conference on Document Analysis and Recognition. 2009. Pр. 1403-1407.Blankers V.L., van den Heuvel C.E., Franke K.Y., Vuurpijl L.G. Icdar 2009 signature verification competition. In: Proceedings of the International Conference on Document Analysis and Recognition. 2009. Pр. 1403-1407.Golub Y.I., Starovoitov V.V. Image quality assessment. Minsk: UIIP NAS Belarus. 2023. 252 p.Golub Y.I., Starovoitov V.V. Image quality assessment. Minsk: UIIP NAS Belarus. 2023. 252 p.Finogeev E.L., Terehova Y.V. Investigation of the dependence of the accuracy of recognition of handwritten signatures from the language group using deep neural networks. The second international scientific and practical forum on economic security "VII VSKEB". 2021. Pр. 97-104.Finogeev E.L., Terehova Y.V. Investigation of the dependence of the accuracy of recognition of handwritten signatures from the language group using deep neural networks. The second international scientific and practical forum on economic security "VII VSKEB". 2021. Pр. 97-104.

The authors declare that there are no conflicts of interest present.