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Title: On the relevance of image acquisition resolution for hand geometry identification based on MLP
Authors: Ferrera, Miguel A. 
Fàbregas, Joan
Faundez-Zanuy, Marcos
Alonso, Jesús B. 
Travieso, Carlos 
Sacristan, Amparo
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Biometrics, Neural networks, Hand-geometry, Resolution
Issue Date: 2009
Publisher: 0922-6389
Journal: Frontiers in Artificial Intelligence and Applications 
Conference: 19th Italian Workshop of the Italian-Society-for-Neural-Network (SIREN) on Neural Nets (WIRN) 
Abstract: The effect of changing the image resolution over a biometric system based on hand geometry is analyzed in this paper. Image resolution is progressively diminished from an initial 120dpi resolution up to 24dpi. The robustness of the examined system is analyzed with 2 databases and two identifiers. The first database acquires the images of the hand underneath whereas the second database acquires the images over the hand. The first classifier identifies with a multiclass support vector machine whereas the second classifier identifies with a neural network with error correction output codes. The four experiments show that an image resolution of 72dpi offers a good trade-off between performance and image resolution for the 15 geometric features used.
ISBN: 9781607500728
ISSN: 0922-6389
DOI: 10.3233/978-1-60750-072-8-314
Source: Frontiers in Artificial Intelligence and Applications[ISSN 0922-6389],v. 204, p. 314-322
Appears in Collections:Actas de congresos
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