  Two sequential camera source identification methods are proposed. Sequential
tests implement a log-likelihood ratio test in an incremental way, thus
enabling a reliable decision with a minimal number of observations. One of our
methods adapts Goljan et al.'s to sequential operation. The second, which
offers better performance in terms of error probabilities and average number of
test observations, is based on treating the alternative hypothesis as a doubly
stochastic model. We also discuss how the standard sequential test can be
corrected to account for the event of weak fingerprints. Finally, we validate
the goodness of our methods with experiments.
