Gaussian Multiscale Aggregation Applied to Segmentation in Hand Biometrics

Santos Sierra, Alberto de and Sánchez Ávila, Carmen and Guerra Casanova, Javier and Bailador del Pozo, Gonzalo (2011). Gaussian Multiscale Aggregation Applied to Segmentation in Hand Biometrics. "Sensors", v. 11 (n. 12); pp. 11141-11156. ISSN 1424-8220. https://doi.org/10.3390/s111211141.

Description

Title: Gaussian Multiscale Aggregation Applied to Segmentation in Hand Biometrics
Author/s:
  • Santos Sierra, Alberto de
  • Sánchez Ávila, Carmen
  • Guerra Casanova, Javier
  • Bailador del Pozo, Gonzalo
Item Type: Article
Título de Revista/Publicación: Sensors
Date: 2011
ISSN: 1424-8220
Volume: 11
Subjects:
Faculty: Centro de Domótica Integral (CeDInt) (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

This paper presents an image segmentation algorithm based on Gaussian multiscale aggregation oriented to hand biometric applications. The method is able to isolate the hand from a wide variety of background textures such as carpets, fabric, glass, grass, soil or stones. The evaluation was carried out by using a publicly available synthetic database with 408,000 hand images in different backgrounds, comparing the performance in terms of accuracy and computational cost to two competitive segmentation methods existing in literature, namely Lossy Data Compression (LDC) and Normalized Cuts (NCuts). The results highlight that the proposed method outperforms current competitive segmentation methods with regard to computational cost, time performance, accuracy and memory usage.

More information

Item ID: 13632
DC Identifier: http://oa.upm.es/13632/
OAI Identifier: oai:oa.upm.es:13632
DOI: 10.3390/s111211141
Official URL: http://www.mdpi.com/1424-8220/11/12/11141
Deposited by: Memoria Investigacion
Deposited on: 16 Oct 2012 07:54
Last Modified: 21 Apr 2016 12:58
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