Artifact-metrics is an automated method of authenticating artifacts based on a measurable intrinsic characteristic.
Intrinsic characters, such as microscopic random-patterns made during the manufacturing process, are very difficult to
copy. A transmitted light image of the distribution can be used for artifact-metrics, since the fiber distribution of paper is
random. Little is known about the individuality of the transmitted light image although it is an important requirement for
intrinsic characteristic artifact-metrics. Measuring individuality requires that the intrinsic characteristic of each artifact
significantly differs, so having sufficient individuality can make an artifact-metric system highly resistant to brute force
attack. Here we investigate the influence of paper category, matching size of sample, and image-resolution on the
individuality of a transmitted light image of paper through a matching test using those images. More concretely, we
evaluate FMR/FNMR curves by calculating similarity scores with matches using correlation coefficients between pairs
of scanner input images, and the individuality of paper by way of estimated EER with probabilistic measure through a
matching method based on line segments, which can localize the influence of rotation gaps of a sample in the case of
large matching size. As a result, we found that the transmitted light image of paper has a sufficient individuality.