  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.
