Fake finger-vein image detection based on Fourier and wavelet transforms

Abstract

Recently, finger-vein recognition has received considerable attention. It is widely used in many applications because of its numerous advantages, such as the small capture device, high accuracy, and user convenience. Nevertheless, finger-vein recognition faces a number of challenges. One critical issue is the use of fake finger-vein images to carry out system attacks. To overcome this problem, we propose a new fake finger-vein image-detection method based on the analysis of finger-vein images in both the frequency and spatial domains. This research is novel in five key ways. First, very little research has been conducted to date on fake finger-vein image detection. We construct a variety of fake finger-vein images, printed on A4 paper, matte paper, and overhead projector film, with which we evaluate the performance of our system. Second, because our proposed method is based on a single captured image, rather than a series of successive images, the processing time is short, no additional image alignment is required, and it is very convenient for users. Third, our proposed method is software-based, and can thus be easily implemented in various finger-vein recognition systems without special hardware. Fourth. Fourier transform features in the frequency domain are used for the detection of fake finger-vein images: further, both spatial and frequency characteristics from Haar and Daubechies wavelet transforms are used for fake finger-vein image detection. Fifth, the detection accuracy of fake finger-vein images is enhanced by combining the features of the Fourier transform and Haar and Daubechies wavelet transforms based on support vector machines. Experimental results indicate that the equal error rate of fake finger-vein image detection with our proposed method is lower than that with a Fourier transform, wavelet transform, or other fusion methods. (C) 2013 Elsevier Inc. All rights reserved.