Authors:
Alberto de Santos Sierra
;
Carmen Sánchez Ávila
;
Javier Guerra Casanova
and
Gonzalo Bailador del Pozo
Affiliation:
Universidad Politécnica de Madrid, Spain
Keyword(s):
Hand segmentation, Fuzzy multiscale aggregation, Biometrics, Hand geometry, Synthetic database.
Related
Ontology
Subjects/Areas/Topics:
Biometrics and Pattern Recognition
;
Image and Video Processing, Compression and Segmentation
;
Multimedia
;
Multimedia and Communications
;
Multimedia Security and Cryptography
;
Multimedia Signal Processing
;
Telecommunications
Abstract:
Applying biometrics to daily scenarios involves demanding requirements in terms of software and hardware. On the contrary, current biometric techniques are also being adapted to present-day devices, like mobile phones, laptops and the like, which are far from meeting the previous stated requirements. In fact, achieving a combination of both necessities is one of the most difficult problems at present in biometrics. Therefore, this paper presents a segmentation algorithm able to provide suitable solutions in terms of precision for hand biometric recognition, considering a wide range of backgrounds like carpets, glass, grass, mud, pavement, plastic, tiles or wood. Results highlight that segmentation accuracy is carried out with high rates of precision (F-measure≥88%)), presenting competitive time results when compared to state-of-the-art segmentation algorithms time performance.