Gaussian Multiscale Aggregation oriented to Hand Biometric Segmentation in Mobile Devices

Santos Sierra, Alberto de and Sánchez Ávila, Carmen and Bailador del Pozo, Gonzalo and Guerra Casanova, Javier (2011). Gaussian Multiscale Aggregation oriented to Hand Biometric Segmentation in Mobile Devices. In: "2011 Third World Congress on Nature and Biologically Inspired Computing (NaBIC)", 19/10/2011 - 21/10/2011, Salamanca, España. ISBN 978-1-4577-1122-0.

Description

Title: Gaussian Multiscale Aggregation oriented to Hand Biometric Segmentation in Mobile Devices
Author/s:
  • Santos Sierra, Alberto de
  • Sánchez Ávila, Carmen
  • Bailador del Pozo, Gonzalo
  • Guerra Casanova, Javier
Item Type: Presentation at Congress or Conference (Article)
Event Title: 2011 Third World Congress on Nature and Biologically Inspired Computing (NaBIC)
Event Dates: 19/10/2011 - 21/10/2011
Event Location: Salamanca, España
Title of Book: Proceeding of 2011 Third World Congress on Nature and Biologically Inspired Computing (NaBIC)
Date: 2011
ISBN: 978-1-4577-1122-0
Subjects:
Faculty: Centro de Domótica Integral (CeDInt) (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

Full text

[img]
Preview
PDF - Requires a PDF viewer, such as GSview, Xpdf or Adobe Acrobat Reader
Download (601kB) | Preview

Abstract

New trends in biometrics are oriented to mobile devices in order to increase the overall security in daily actions like bank account access, e-commerce or even document protection within the mobile. However, applying biometrics to mobile devices imply challenging aspects in biometric data acquisition, feature extraction or private data storage. Concretely, this paper attempts to deal with the problem of hand segmentation given a picture of the hand in an unknown background, requiring an accurate result in terms of hand isolation. For the sake of user acceptability, no restrictions are done on background, and therefore, hand images can be taken without any constraint, resulting segmentation in an exigent task. Multiscale aggregation strategies are proposed in order to solve this problem due to their accurate results in unconstrained and complicated scenarios, together with their properties in time performance. This method is evaluated with a public synthetic database with 480000 images considering different backgrounds and illumination environments. The results obtained in terms of accuracy and time performance highlight their capability of being a suitable solution for the problem of hand segmentation in contact-less environments, outperforming competitive methods in literature like Lossy Data Compression image segmentation (LDC).

More information

Item ID: 13544
DC Identifier: http://oa.upm.es/13544/
OAI Identifier: oai:oa.upm.es:13544
Official URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6089603
Deposited by: Memoria Investigacion
Deposited on: 17 Oct 2012 09:22
Last Modified: 21 Apr 2016 12:51
  • Logo InvestigaM (UPM)
  • Logo GEOUP4
  • Logo Open Access
  • Open Access
  • Logo Sherpa/Romeo
    Check whether the anglo-saxon journal in which you have published an article allows you to also publish it under open access.
  • Logo Dulcinea
    Check whether the spanish journal in which you have published an article allows you to also publish it under open access.
  • Logo de Recolecta
  • Logo del Observatorio I+D+i UPM
  • Logo de OpenCourseWare UPM