Forearm vein pattern recognition using features from visible and NIR images

Abstract

Forearm vein recognition is one of many available methods used for identification. However, forearm veins can be considered more secure compared to other biometric traits because the veins are inside the human body and therefore not easily manipulated. Veins possess several properties that make a good biometric feature for personal identification: 1) they are difficult to damage and modify; 2) they are difficult to simulate using a fake template; and 3) vein information can represent the liveness of person. Features were extracted from each pair of visible and NIR images. For the visible images, feature extraction was done using the Gabor filter. For the NIR forearm images, a crossing number was used to extract properties of the veins e.g. bifurcation. We present the results of the recognition of forearm veins patterns that show the suitability of the method for biometric identification purposes.