Geodesic
Robust fingerprint flow chart algorithm
Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ Vyčislitelʹnaâ matematika i informatika, Tome 8 (2019) no. 4, pp. 43-55

Voir la notice de l'article provenant de la source Math-Net.Ru

The orientation field is an important characteristic of human skin patterns and has a significant impact on the results of fingerprint identification. The methods of constructing the orientation field based on the gradient are diverse, but they are united by a high sensitivity to noise and defects that appear on the images during the formation of tracks. The article proposes a new method for constructing a stream field for digital images of fingerprints. The method allows to improve the solution of a number of key tasks of image processing, including the task of predicting the direction of lines in the area of skin folds, scars and other finger surface defects. The method relies on such approaches as image processing at the subpixel level, on cluster analysis of the field of image gradients and consists in the sequential application of several algorithms. These are image interpolation and estimation of gradient values on it, convolution of the gradient field with a given pattern for noise control at the subpixel level, selection of reference areas based on the construction of local quality estimates of the pattern, prediction of the direction field from reference areas over the entire image with the adaptation of the predicted values for the measurement results. The results of the proposed method were verified using the web framework created on the basis of the University of Bologna in Italy. The new verification results are compared with the verification results of the earlier method developed by the authors, and with other published algorithms on the same web framework.
Keywords: biometrical identification, fingerprint orientation field, pattern recognition, fingerprints, verification. 
@article{VYURV_2019_8_4_a3,
     author = {A. V. Agafonov and D. S. Rozhina and H. I. Wahhab and A. N. Alanssari},
     title = {Robust fingerprint flow chart algorithm},
     journal = {Vestnik \^U\v{z}no-Uralʹskogo gosudarstvennogo universiteta. Seri\^a Vy\v{c}islitelʹna\^a matematika i informatika},
     pages = {43--55},
     publisher = {mathdoc},
     volume = {8},
     number = {4},
     year = {2019},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/VYURV_2019_8_4_a3/}
}
TY  - JOUR
AU  - A. V. Agafonov
AU  - D. S. Rozhina
AU  - H. I. Wahhab
AU  - A. N. Alanssari
TI  - Robust fingerprint flow chart algorithm
JO  - Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ Vyčislitelʹnaâ matematika i informatika
PY  - 2019
SP  - 43
EP  - 55
VL  - 8
IS  - 4
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/VYURV_2019_8_4_a3/
LA  - ru
ID  - VYURV_2019_8_4_a3
ER  - 
%0 Journal Article
%A A. V. Agafonov
%A D. S. Rozhina
%A H. I. Wahhab
%A A. N. Alanssari
%T Robust fingerprint flow chart algorithm
%J Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ Vyčislitelʹnaâ matematika i informatika
%D 2019
%P 43-55
%V 8
%N 4
%I mathdoc
%U http://geodesic.mathdoc.fr/item/VYURV_2019_8_4_a3/
%G ru
%F VYURV_2019_8_4_a3
A. V. Agafonov; D. S. Rozhina; H. I. Wahhab; A. N. Alanssari. Robust fingerprint flow chart algorithm. Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ Vyčislitelʹnaâ matematika i informatika, Tome 8 (2019) no. 4, pp. 43-55. http://geodesic.mathdoc.fr/item/VYURV_2019_8_4_a3/