Hand Image Segmentation by Means of Gaussian Multiscale Aggregation for Biometric Apllications

Descripción (resumen): 

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.


Tipo publicación: 
Congreso
Publicado en: 
International Conference on Signal Processing and Multimedia Applications (SIGMAP), 2011 Sevilla, Spain. Proceedings of the International Conference on Signal Processing and Multimedia Applications (SIGMAP) 2011 p.p.40-46
ISBN/ISSN: 
978-989-8425-72-0
Biometría bioseñales y seguridad
Fecha de Publicacion: 
Julio 2011
Autores CeDInt: