The number of medicine counterfeits increases each year due to the accessibility of printing devices and the weak protection of medicine blister foils. The medicine blisters are often produced using the rotogravure printing process. In this paper, we address the problem of rotogravure press identification and printed support identification using similarity metric learning. Both identification problems are difficult as the impact of printing press or of printing support are minimal, moreover the classical techniques (for example, the use of Pearson correlation) cannot identify the rotogravure press or the printing support used for the packaging production. We show that the similarity metric learning can easily identify the press used and the printing support used. Additionally, we explore the possibility to use the proposed approach for packaging authentication.