A Finger Vein Image-Based Personal Identification System With Self-Adaptive Illuminance Control
As a biometric trait, finger vein pattern-based technology is highly effective for personal identification with high security. In this paper, we presented the design of a personal identification system based on near infrared (NIR) finger vein image. In this paper, we introduced an observation model of finger vein imaging, upon which a self-adaptive illuminance control algorithm is proposed and integrated into image acquisition hardware. According to the distribution of pixel intensity of the acquired image, the proposed algorithm could automatically adjust the illuminance distribution of lighting: increase the illuminance of lighting, under which the thicker part of finger body is presented and decrease the illuminance of lighting, under which the thinner part of finger body is presented. With this adaptation, the whole finger body could be illuminated appropriately according to its thickness distribution, and the overexposure and underexposure are avoided effectively. An NIR finger vein image database containing 2040 images is established and published in this paper. In the image preprocessing stage, Gabor filters are used to enhance captured raw finger vein images. In our experiment, the identification performance of our system is evaluated using the recognition rate and the margin distribution. A sparse representation-based algorithm is used to calculate the recognition rate and provide data for margin analysis. The results prove the effectiveness of the proposed illuminance control algorithm and the whole system in finger vein-based personal identification.
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