KFU. Card publication. Web Application for Capturing Biometric Features of Handwriting on Mobile Devices

KAZAN
FEDERAL UNIVERSITY

- RUS
- 中文
- ES

WEB APPLICATION FOR CAPTURING BIOMETRIC FEATURES OF HANDWRITING ON MOBILE DEVICES

Form of presentation

Articles in international journals and collections

Year of publication

2026

��

��

Authors, employees of KFU

Bayanov Bulat Ilmirovich, author

Ismagilov Ilyas Idrisovich, author

Bibliographic description in the original language

Bayanov, Ismagilov, Web Application for Capturing Biometric Features of Handwriting on Mobile Devices//Lecture Notes in Electrical Engineering. - 2026. - Vol.1521 LNEE, Is.. - P.448-455.

Annotation

As part of the research on biometric features of handwriting, a specialized web application was developed to capture data about touch events on smartphones touchscreen. The application was implemented using HTML5 and JavaScript with the Canvas element to create an interactive input area. The study involved 40 participants, each of whom entered the same random three-character handwritten passphrase 25 times. The study focuses on random forgeries only. The biometric data of handwriting was recorded on a Redmi Note 9 Pro device (rate of touch sampling at 60 Hz), with the additional ability to capture biometric features such as: coordinates, timestamps, touch contact area and touchscreen pressure sensitivity. Biometric data of random signatures are stored in Excel document format, which are further processed by tools of the Python programming language. For comparison, the article presents tables of results and graphs demonstrating the similarity of biometric features of handwriting with the public available database of signatures SVC2004. The developed web application can be used by scientific researchers, preferably with citation to this work.

Keywords

biometrics, biometric features, handwriting, pattern recognition, mobile device, web application

The name of the journal

Lecture Notes in Electrical Engineering

URL

https://link.springer.com/chapter/10.1007/978-3-032-14742-4_39

Please use this ID to quote from or refer to the card

https://repository.kpfu.ru/eng/?p_id=323154&p_lang=2

Full metadata record

Field DC	Value	Language
dc.contributor.author	Bayanov Bulat Ilmirovich	ru_RU
dc.contributor.author	Ismagilov Ilyas Idrisovich	ru_RU
dc.date.accessioned	2026-01-01T00:00:00Z	ru_RU
dc.date.available	2026-01-01T00:00:00Z	ru_RU
dc.date.issued	2026	ru_RU
dc.identifier.citation	Bayanov, Ismagilov, Web Application for Capturing Biometric Features of Handwriting on Mobile Devices//Lecture Notes in Electrical Engineering. - 2026. - Vol.1521 LNEE, Is.. - P.448-455.	ru_RU
dc.identifier.uri	https://repository.kpfu.ru/eng/?p_id=323154&p_lang=2	ru_RU
dc.description.abstract	Lecture Notes in Electrical Engineering	ru_RU
dc.description.abstract	As part of the research on biometric features of handwriting, a specialized web application was developed to capture data about touch events on smartphones touchscreen. The application was implemented using HTML5 and JavaScript with the Canvas element to create an interactive input area. The study involved 40 participants, each of whom entered the same random three-character handwritten passphrase 25 times. The study focuses on random forgeries only. The biometric data of handwriting was recorded on a Redmi Note 9 Pro device (rate of touch sampling at 60 Hz), with the additional ability to capture biometric features such as: coordinates, timestamps, touch contact area and touchscreen pressure sensitivity. Biometric data of random signatures are stored in Excel document format, which are further processed by tools of the Python programming language. For comparison, the article presents tables of results and graphs demonstrating the similarity of biometric features of handwriting with the public available database of signatures SVC2004. The developed web application can be used by scientific researchers, preferably with citation to this work.	ru_RU
dc.language.iso	ru	ru_RU
dc.subject	biometrics	ru_RU
dc.subject	biometric features	ru_RU
dc.subject	handwriting	ru_RU
dc.subject	pattern recognition	ru_RU
dc.subject	mobile device	ru_RU
dc.subject	web application	ru_RU
dc.title	Web Application for Capturing Biometric Features of Handwriting on Mobile Devices	ru_RU
dc.type	Articles in international journals and collections	ru_RU