  Paper surfaces under the microscopic view are observed to be formed by
intertwisted wood fibers. Such structures of paper surfaces are unique from one
location to another and are almost impossible to duplicate. Previous work used
microscopic surface normals to characterize such intrinsic structures as a
"fingerprint" of paper for security and forensic applications. In this work, we
examine several key research questions of feature extraction in both scientific
and engineering aspects to facilitate the deployment of paper surface-based
authentication when flatbed scanners are used as the acquisition device. We
analytically show that, under the unique optical setup of flatbed scanners, the
specular reflection does not play a role in norm map estimation. We verify,
using a larger dataset than prior work, that the scanner-acquired norm maps,
although blurred, are consistent with those measured by confocal microscopes.
We confirm that, when choosing an authentication feature, high
spatial-frequency subbands of the heightmap are more powerful than the norm
map. Finally, we show that it is possible to empirically calculate the physical
dimensions of the paper patch needed to achieve a certain authentication
performance in equal error rate (EER). We analytically show that log(EER) is
decreasing linearly in the edge length of a paper patch.
