On Generating Cancelable Biometric Template using Reverse of Boolean XOR

Abstract

Cancelable Biometric is repetitive distortion embedded in original Biometric image for keeping it secure from unauthorized access. In this paper, we have generated Cancelable Biometric templates with Reverse Boolean XOR technique. Three different methods have been proposed for generation of Cancelable Biometric templates based on Visual Secret Sharing scheme. In each method, one Secret image and n-1 Cover images are used as: (M1) One original Biometric image (Secret) with n- 1 randomly chosen Gray Cover images (M2) One original Secret image with n-1 Cover images, which are Randomly Permuted version of the original Secret image (M3) One Secret image with n-1 Cover images, both Secret image and Cover images are Randomly Permuted version of original Biometric image. Experiment works have performed on publicly available ORL Face database and IIT Delhi Iris database. The performance of the proposed methods is compared in terms of Co-relation Coefficient (Cr), Mean Square Error (MSE), Mean Absolute Error (MAE), Structural Similarity (SSIM), Peak Signal to Noise Ratio (PSNR), Number of Pixel Change Rate (NPCR), and Unified Average Changing Intensity (UACI). It is found that among the three proposed method, M3 generates good quality Cancelable templates and gives best performance in terms of quality. M3 is also better in quantitative terms on ORL dataset while M2 and M3 are comparable on IIT Delhi Iris dataset.