Liveness Detection of Dorsal Hand Vein Based on the Analysis of Fourier Spectral

Liveness detection of dorsal hand vein is a necessary step towards higher reliability of identification and is attracting increasing attention of researchers. However, there’s only few published research in this area. This paper proposes a novel method for liveness detection of dorsal hand vein. First, by applying the Fourier Transform, a feature is extracted as a statistical value of spectral energy derived from every blocked spectrum of single wavelength infrared images. Second, regarding the principle of blocking, massive experiments have been performed to find the optimum feature with the maxmin criterion. Furthermore, an SVM classifier is employed for clustering. The experimental results have verified the effectiveness of our proposed method.

[1]  Christos Faloutsos,et al.  Efficient Similarity Search In Sequence Databases , 1993, FODO.

[2]  Stan Z. Li,et al.  Face liveness detection by learning multispectral reflectance distributions , 2011, Face and Gesture 2011.

[3]  Ronen Basri,et al.  Lambertian Reflectance and Linear Subspaces , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Chien-Chung Shen,et al.  A Graph Matching Approach to Optimal Task Assignment in Distributed Computing Systems Using a Minimax Criterion , 1985, IEEE Trans. Computers.

[5]  Anil K. Jain,et al.  Handbook of Fingerprint Recognition , 2005, Springer Professional Computing.

[6]  David B. Lomet,et al.  Foundations of Data Organization and Algorithms , 1993, Lecture Notes in Computer Science.

[7]  Eugene Sweeney Veincheck - A technical perspective , 1998, Inf. Secur. Tech. Rep..