Patrick Takenaka
Publication
Classification of Inkjet Printers based on Droplet Statistics
We are happy to share that our PhD students Patrick Takenaka, Manuel Eberhardinger, and Daniel Grießhaber presented their joint work on Classification of Inkjet Printers based on Droplet Statistics at the IEEE World Congress on Computational Intelligence in Yokohama, Japan.
Abstract
Knowing the printer model used to print a given document may provide a crucial lead towards identifying counterfeits or conversely verifying the validity of a real document. Inkjet printers produce probabilistic droplet patterns that appear to be distinct for each printer model and as such we investigate the utilization of droplet characteristics including frequency domain features extracted from printed document scans for the classification of the underlying printer model. We collect and publish a dataset of high resolution document scans and show that our extracted features are informative enough to enable a neural network to distinguish not only the printer manufacturer, but also individual printer models.
Authors: Patrick Takenaka, Manuel Eberhardinger, Daniel Grießhaber, Johannes Maucher
Link to paper (preprint): https://arxiv.org/abs/2407.09539
