KaydedilenlerDerginizi ekleyin

Dergiler / Turkish Journal of Electrical Engineering and Computer Science / 2009 / Cilt: 17 - Sayı: 2

An intelligent face features generation system from fingerprints

Şeref SAĞIROĞLU
Necla ÖZKAYA
Sayfa
183–203
Yayın Tarihi
2009-02-01
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

It can be concluded that the proposed study significantly and directly contributes to biometrics and its new applications.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:In this study, a novel intelligent system based on artificial neural networks was designed and introduced for generating faces from fingerprints with high accuracy.
📊
Temel Bulgular & Veri:The proposed system has a number of modules including two feature enrolment modules for acquiring the fingerprints and faces into the system, two feature extractors for extracting the feature sets of fingerprint and face biometrics, an artificial neural network module that was configured with the help of Taguchi experimental design method for establishing relationships among the biometric features, a face re-constructor for building up face features from the results of the system, and a test module for test the results of the system. 10-fold cross validation technique was used for evaluating the performance of the system.
💡
Sonuç & Katkı:It can be concluded that the proposed study significantly and directly contributes to biometrics and its new applications.
🔬Tür:Araştırma Makalesi
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Information security · biometrics · artificial neural networks.

Özet

In this study, a novel intelligent system based on artificial neural networks was designed and introduced for generating faces from fingerprints with high accuracy. The proposed system has a number of modules including two feature enrolment modules for acquiring the fingerprints and faces into the system, two feature extractors for extracting the feature sets of fingerprint and face biometrics, an artificial neural network module that was configured with the help of Taguchi experimental design method for establishing relationships among the biometric features, a face re-constructor for building up face features from the results of the system, and a test module for test the results of the system. 10-fold cross validation technique was used for evaluating the performance of the system. The results have shown that the face features can be successfully generated from only fingerprints. It can be concluded that the proposed study significantly and directly contributes to biometrics and its new applications.

Abstract

In this study, a novel intelligent system based on artificial neural networks was designed and introduced for generating faces from fingerprints with high accuracy. The proposed system has a number of modules including two feature enrolment modules for acquiring the fingerprints and faces into the system, two feature extractors for extracting the feature sets of fingerprint and face biometrics, an artificial neural network module that was configured with the help of Taguchi experimental design method for establishing relationships among the biometric features, a face re-constructor for building up face features from the results of the system, and a test module for test the results of the system. 10-fold cross validation technique was used for evaluating the performance of the system. The results have shown that the face features can be successfully generated from only fingerprints. It can be concluded that the proposed study significantly and directly contributes to biometrics and its new applications.

🔖

Bu Makaleye Atıf Yap

SAĞIROĞLU, Ş., ÖZKAYA, N. (2009). An intelligent face features generation system from fingerprints. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 17 - Sayı: 2, 183–203. https://ajindex.com/articles/189087

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (9)

  1. Jain, A.K., Pankanti, S., Prabhakar, S., Hong, L., Ross, A., Wayman, J.L., Biometrics: A Grand Challenge, In Proceedings of the International Conference on Pattern Recognition, Cambridge, UK, August, vol. 2, pp. 935-942 (2004)
  2. Maio, D., Maltoni, D., Jain A.K., Prabhakar, S., Handbook of Şngerprint recognition, Springer-Verlag, New York, (2003)
  3. Jain, L.C., Halici, U., Hayashi, I., Lee, S.B., Tsutsui, S., Intelligent biometric techniques in Şngerprint and face recognition, CRC press, New York (1999)
  4. Ozkaya, N., Sagiroglu, S., Intelligent Face Border Generation System from Fingerprints, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2008) in IEEE World Congress on Computational Intelligence (WCCI ), IEEE Catalog number: CFP08FUZ-CDR, ISBN: 978-1-4244-1819-0, ISSN: 1098-7584, Congress: 2007907698, 6 June 2008,
  5. Hong Kong. Sagiroglu, S., Ozkaya, N., An Intelligent Automatic Face Contour Prediction System, Advances in ArtiŞcial Intelligence, The 21. Canadian Conference on ArtiŞcial Intelligence (AI 2008), Lecture Notes in Computer Science (LNCS), Springer Berlin / Heidelberg, ISSN: 0302-9743 (Print) 1611-3349 (Online), ISBN 978-3-540-68821-1, Volume: 5032/2008, Pages 246-258, (DOI 10.1007/978-3-540-68825-9 24), 28-30 May 2008,
  6. Ontario, Canada. Sagiroglu, S., Ozkaya, N., An Intelligent Automatic Face Model Prediction System, International Conference on Multivariate Statistical Modelling & High Dimensional Data Mining (HDM 2008), 19-23 June 2008,
  7. Kayseri, Turkey. Ozkaya, N., Sagiroglu, S., Intelligent Face Mask Prediction System, International Joint Conference on Neural Networks (IJCNN 2008) in IEEE World Congress on Computational Intelligence (WCCI 2008), IEEE Catalog number: CFP08IJS-CDR, ISBN: 978-1-4244-1821-3, ISSN: 1098-7576, Library of Congress: 2007907698, 1-6 June 2008,
  8. Hong Kong. Ozkaya, N., Sagiroglu, S., Translating the Fingerprints to the Faces: A New Approach, IEEE 16th Signal Processing, Communication and Applications Conference (Siu 2008), IEEE Catalog number: CFP08559 – CDR, ISBN: 978-1 1999-9, Library of Congress: 2007943521, 20-22 April 2008,
  9. Turkey. Sagiroglu, S., Ozkaya, N., ArtiŞcial Neural Network Based Automatic Face Model Generation System from Only One Fingerprint, The Third International Workshop on ArtiŞcial Neural Networks in Pattern Recognition (ANNPR), Lecture Notes in Computer Science (LNCS), Springer Berlin / Heidelberg, ISSN: 0302-9743 (Print), 1611-3349 (Online), Vol. 5064, DOI: 10.1007/978-3-540-69939-2, ISBN: 978-3-54