Near-Optimal Time Function for Secure Dynamic Visual Cryptography

The strategy for the selection of an optimal time function for dynamic visual cryptography is presented in this paper. Evolutionary algorithms are used to obtain the symmetric piece-wise uniform density function. The fitness function of each chromosome is associated with the derivative of the standard of the time-averaged moiré image. The reconstructed near-optimal time function represents the smallest interval of amplitudes where an interpretable moiré pattern is generated in the time-averaged image. Such time functions can be effectively exploited in computational implementation of secure dynamic visual cryptography.