Open AccessFlooding‐based segmentation for contactless hand biometrics oriented to mobile devices
Author(s) -
Bailador Gonzalo,
RíosSánchez Belén,
SánchezReillo Raúl,
Ishikawa Hiroshi,
SánchezÁvila Carmen
Publication year - 2018
Publication title -
iet biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 28
eISSN - 2047-4946
pISSN - 2047-4938
DOI - 10.1049/iet-bmt.2017.0166
Subject(s) - computer science , biometrics , flooding (psychology) , segmentation , computer security , mobile device , artificial intelligence , world wide web , computer vision , psychology , psychotherapist
Segmentation is a crucial stage in hand biometric recognition due to its direct influence on the feature extraction process. The actual trend toward contactless biometrics adds new challenges to traditional defiances, which are mainly related to the capturing conditions and the limitations on computational resources. Traditional methods do not succeed when variable capturing conditions are imposed and methods which are able to deal with daily‐life situations are, in general, computationally expensive. In this study, a competitive flooding‐based segmentation method oriented to mobile devices is proposed in order to achieve a compromised solution between accuracy and computational resources consumption. The method has been evaluated using images coming from five different databases which cover a wide spectrum of capturing conditions, one of them recorded as a part of this study. The results have been compared with other two well known segmentation techniques in terms of both accuracy and computation time.