Skoči na glavni sadržaj

Izvorni znanstveni članak

https://doi.org/10.17559/TV-20170816124949

Novel Feature Extraction Methodology with Evaluation in Artificial Neural Networks Based Fingerprint Recognition System

Nihan Kahraman orcid id orcid.org/0000-0003-1623-3557 ; Yildiz Technical University, Department of Electronics and Communications Engineering, 34349 Beşiktaş – İstanbul / TURKEY
Zehra Gulru Cam Taskiran ; Yildiz Technical University, Department of Electronics and Communications Engineering, 34349 Beşiktaş – İstanbul / TURKEY
Murat Taskiran ; Yildiz Technical University, Department of Electronics and Communications Engineering, 34349 Beşiktaş – İstanbul / TURKEY


Puni tekst: engleski pdf 1.440 Kb

str. 112-119

preuzimanja: 934

citiraj


Sažetak

Fingerprint recognition is one of the most common biometric recognition systems that includes feature extraction and decision modules. In this work, these modules are achieved via artificial neural networks and image processing operations. The aim of the work is to define a new method that requires less computational load and storage capacity, can be an alternative to existing methods, has high fault tolerance, convenient for fraud measures, and is suitable for development. In order to extract the feature points called minutia points of each fingerprint sample, Multilayer Perceptron algorithm is used. Furthermore, the center of the fingerprint is also determined using an improved orientation map. The proposed method gives approximate position information of minutiae points with respect to the core point using a fairly simple, orientation map-based method that provides ease of operation, but with the use of artificial neurons with high fault tolerance, this method has been turned to an advantage. After feature extraction, General Regression Neural Network is used for identification. The system algorithm is evaluated in UPEK and FVC2000 database. The accuracies without rejection of bad images for the database are 95.57% and 91.38% for UPEK and FVC2000 respectively.

Ključne riječi

Artificial Intelligence; Feature Extraction; Fingerprint Recognition; Neural Networks

Hrčak ID:

200606

URI

https://hrcak.srce.hr/200606

Datum izdavanja:

26.5.2018.

Posjeta: 1.938 *