Finger-Vein Cancelable Template Protection based on Random Permutation Projection

Abstract

The uniform random permutation hash (URP) algorithm has reliable irreversibility in the protection of biometrics template. However, by randomly permutation of feature vectors and calculation of dot product, URP method cannot completely retain the global information of the original feature vectors, it will affect the recognition rate of algorithm. Yet it’s important for recognition rate in biometrics cancelable template, therefore this paper proposed a new finger-vein cancelable template named random permutation projection (RPP). First, the random permutation matrix is generated by combining users’ token matrix with original feature vector. Second, the projection vector is obtained by multiplying original feature vector with random permutation matrix, we also record the maximum and sub-large index in projection vector. At last, the sub-large index is considered integrating with maximum index, this will significantly reduce error by only considering one index. The experimental results show that the RPP template improved the recognition rate of the algorithm on the PolyU and SDUMLA-FV data sets, RPP also meets the revocability standard of cancelable biometric templates.