Dynamic ROI Extraction for Palmprints using MediaPipe Hands
Küçük Resim Yok
Tarih
2022
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Hand-based biometric traits have been widely used in recognition systems. Dynamic region of interest extraction is an important preprocessing step for these systems to avoid recognition performance degradation. In this study, a dynamic region of interest extraction method that can be used for palm vein, palmprint, and dorsal hand vein has been proposed using Google's MediaPipe Hands framework. Since 3 biometric traits focus on nearly the same region that contains biometric information on the images, this study aims to show that the proposed extraction method can be utilized for these traits on mobile biometric applications. This method has been implemented on IIT Delhi Touchless Palmprint Database and 93% accuracy was obtained. The average processing time per image for ROI extraction was recorded as 2.64 seconds. With this study, a paradigm for future studies on hand biometrics has been created and the required processing time for a dynamic extraction has been reduced considerably.
Açıklama
30th IEEE Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2022 -- Safranbolu, TURKEY
Anahtar Kelimeler
palmprint, dynamic extraction, region of interest, MediaPipe Hands, preprocessing
Kaynak
2022 30Th Signal Processing and Communications Applications Conference, Siu
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
