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

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

Nihan Kahraman   ORCID icon 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 MB) str. 112-119 preuzimanja: 371* citiraj
APA 6th Edition
Kahraman, N., Cam Taskiran, Z.G. i Taskiran, M. (2018). Novel Feature Extraction Methodology with Evaluation in Artificial Neural Networks Based Fingerprint Recognition System. Tehnički vjesnik, 25 (Supplement 1), 112-119. https://doi.org/10.17559/TV-20170816124949
MLA 8th Edition
Kahraman, Nihan, et al. "Novel Feature Extraction Methodology with Evaluation in Artificial Neural Networks Based Fingerprint Recognition System." Tehnički vjesnik, vol. 25, br. Supplement 1, 2018, str. 112-119. https://doi.org/10.17559/TV-20170816124949. Citirano 17.10.2019.
Chicago 17th Edition
Kahraman, Nihan, Zehra Gulru Cam Taskiran i Murat Taskiran. "Novel Feature Extraction Methodology with Evaluation in Artificial Neural Networks Based Fingerprint Recognition System." Tehnički vjesnik 25, br. Supplement 1 (2018): 112-119. https://doi.org/10.17559/TV-20170816124949
Harvard
Kahraman, N., Cam Taskiran, Z.G., i Taskiran, M. (2018). 'Novel Feature Extraction Methodology with Evaluation in Artificial Neural Networks Based Fingerprint Recognition System', Tehnički vjesnik, 25(Supplement 1), str. 112-119. https://doi.org/10.17559/TV-20170816124949
Vancouver
Kahraman N, Cam Taskiran ZG, Taskiran M. Novel Feature Extraction Methodology with Evaluation in Artificial Neural Networks Based Fingerprint Recognition System. Tehnički vjesnik [Internet]. 2018 [pristupljeno 17.10.2019.];25(Supplement 1):112-119. https://doi.org/10.17559/TV-20170816124949
IEEE
N. Kahraman, Z.G. Cam Taskiran i M. Taskiran, "Novel Feature Extraction Methodology with Evaluation in Artificial Neural Networks Based Fingerprint Recognition System", Tehnički vjesnik, vol.25, br. Supplement 1, str. 112-119, 2018. [Online]. https://doi.org/10.17559/TV-20170816124949

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

Posjeta: 615 *