Hand Image Segmentation by means of Gaussian Multiscale Aggregation for biometric applications

Santos Sierra, Alberto de and Sánchez Ávila, Carmen and Guerra Casanova, Javier and Bailador del Pozo, Gonzalo (2011). Hand Image Segmentation by means of Gaussian Multiscale Aggregation for biometric applications. In: "International Conference on Signal Processing and Multimedia Applications (SIGMAP) 2011", 18/07/2011 - 21/07/2011, Sevilla, España.

Description

Title: Hand Image Segmentation by means of Gaussian Multiscale Aggregation for biometric applications
Author/s:
  • Santos Sierra, Alberto de
  • Sánchez Ávila, Carmen
  • Guerra Casanova, Javier
  • Bailador del Pozo, Gonzalo
Item Type: Presentation at Congress or Conference (Article)
Event Title: International Conference on Signal Processing and Multimedia Applications (SIGMAP) 2011
Event Dates: 18/07/2011 - 21/07/2011
Event Location: Sevilla, España
Title of Book: Proceedings of the International Conference on Signal Processing and Multimedia Applications (SIGMAP) 2011
Date: 2011
Subjects:
Faculty: Centro de Domótica Integral (CeDInt) (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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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

More information

Item ID: 13478
DC Identifier: http://oa.upm.es/13478/
OAI Identifier: oai:oa.upm.es:13478
Deposited by: Memoria Investigacion
Deposited on: 18 Oct 2012 09:21
Last Modified: 21 Apr 2016 12:48
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