Open AccessDynamic ROI extraction method for hand vein images
Author(s) -
Damak Wafa,
Boukhris Trabelsi Randa,
Alima Damak Masmoudi,
Sellami Dorra
Publication year - 2018
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2017.0613
Subject(s) - computer science , region of interest , segmentation , artificial intelligence , pattern recognition (psychology) , image segmentation , computer vision , orientation (vector space) , mathematics , geometry
The region of interest (ROI) extraction is important in hand vein recognition system. The main challenges for accurate extraction of the vein region are to overcome variability in hand size, lighting conditions, orientation, appearance, noisy background, and non‐uniform grey levels in foreground region. Here, we propose a new dynamic hand vein ROI extraction, preserving the whole vein area. A hand segmentation process robust to the mentioned challenges, contributing to an accurate definition of hand edge delimitations is proposed. Our approach is validated on both dorsal vein Bosphorus database and palm vein Vera database. Our proposed method accuracy is ∼98% for Bosphorus database and 90% for Vera database. To illustrate the efficiency of the proposed ROI extraction, we insert it as a first block in a hand vein recognition system. Then, a comparison study at system level with recent approaches is carried on, showing an improvement of the whole system area under the curve by a rate of 12% and 2% for Bosphorus and Vera databases, respectively. The speed performances demonstrate a mean run time of 0.73 s for Bosphorus database and 1.2 s for Vera database, proving that the proposed method can be conveniently used on a real‐time application.