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Proceedings Paper

Analysis of the hand vein pattern for people recognition
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Paper Abstract

The shape of the hand vascular pattern contains useful and unique features that can be used for identifying and authenticating people, with applications in access control, medicine and financial services. In this work, an optical system for the image acquisition of the hand vascular pattern is implemented. It consists of a CCD camera with sensitivity in the IR and a light source with emission in the 880 nm. The IR radiation interacts with the desoxyhemoglobin, hemoglobin and water present in the blood of the veins, making possible to see the vein pattern underneath skin. The segmentation of the Region Of Interest (ROI) is achieved using geometrical moments locating the centroid of an image. For enhancement of the vein pattern we use the technique of Histogram Equalization and Contrast Limited Adaptive Histogram Equalization (CLAHE). In order to remove unnecessary information such as body hair and skinfolds, a low pass filter is implemented. A method based on geometric moments is used to obtain the invariant descriptors of the input images. The classification task is achieved using Artificial Neural Networks (ANN) and K-Nearest Neighbors (K-nn) algorithms. Experimental results using our database show a percentage of correct classification, higher of 86.36% with ANN for 912 images of 38 people with 12 versions each one.

Paper Details

Date Published: 22 September 2015
PDF: 10 pages
Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 95992Q (22 September 2015); doi: 10.1117/12.2188817
Show Author Affiliations
R. Castro-Ortega, Univ. Politécnica de Tulancingo (Mexico)
C. Toxqui-Quitl, Univ. Politécnica de Tulancingo (Mexico)
G. Cristóbal, Instituto de Óptica "Daza de Valdés" (Spain)
J. Victor Marcos, Instituto de Óptica "Daza de Valdés" (Spain)
A. Padilla-Vivanco, Univ. Politécnica de Tulancingo (Mexico)
R. Hurtado Pérez, Univ. Politécnica de Tulancingo (Mexico)


Published in SPIE Proceedings Vol. 9599:
Applications of Digital Image Processing XXXVIII
Andrew G. Tescher, Editor(s)

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