Palmprint recognition system based on deep region of interest features with the aid of hybrid approach
Yükleniyor...
Dosyalar
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
SpringerLink
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Palmprint recognition system is a biometric technology, which is promising to have a high precision. This system has started
to attract the attention of researchers, especially with the emergence of deep learning techniques in recent years. In this
study, a deep learning and machine learning-based hybrid approach has been recommended to recognize palmprint images
automatically via region of interest (ROI) features. The proposed work consists of several stages, respectively. In the first
stage, the raw images have been collected from the PolyU database and preprocessing operations have been implemented in
order to determine ROI areas. In the second stage, deep ROI features have been extracted from the preprocessed images with
the aid of deep learning technique. In the last stage, the obtained deep features have been classified by employing a hybrid
deep convolutional neural network and support vector machine models. Finally, it has been observed that the overall accuracy
of the proposed system has achieved very successful results as 99.72% via hybrid approach. Moreover, very low execution
time has been observed for whole process of the proposed system with 0.10 s.
Açıklama
Anahtar Kelimeler
Palmprint · ROI · Deep learning · CNN · SVM
Kaynak
Signal, Image and Video Processing
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Türk, Ö., Çalışkan, A., Acar, E., & Ergen, B. (2023). Palmprint recognition system based on deep region of interest features with the aid of hybrid approach. Signal, Image and Video Processing, 1-9.
